Commit Graph

3372 Commits

Author SHA1 Message Date
emanrissha
cbcb1a2bd2
Update marian.md
This update improves the Marian model card to follow the Hugging Face standardized model card format. The changes include:

- Added a clear description of MarianMT, its architecture, and how it differs from other models.
- Provided usage examples for Pipeline and AutoModel.
- Added a quantization example for optimizing model inference.
- Included instructions and examples for multilingual translation with language codes.
- Added an Attention Mask Visualizer example.
- Added a Resources section with relevant links to papers, the Marian framework, language codes, tokenizer guides, and quantization documentation.
- Fixed formatting issues in the code blocks for correct rendering.

This update improves the readability, usability, and consistency of the Marian model documentation for users.
2025-06-30 23:28:24 +03:00
Yao Matrix
29a3f5ed8c
switch default xpu tp backend to pytorch built-in XCCL from pytorch 2.8 (#39024)
* switch default xpu tp backend to pytorch built-in XCCL from pytorch 2.8

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* Update docs/source/en/perf_infer_gpu_multi.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update perf_infer_gpu_multi.md

* Update perf_infer_gpu_multi.md

* Update perf_infer_gpu_multi.md

---------

Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-30 08:54:05 -07:00
jiqing-feng
03db2700ab
Enable XPU doc (#38929)
* fix example with dataset

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update torchao doc

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update torchao doc

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix device type

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* revert torchao change

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix torchao doc

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* revert torchao change

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update xpu torchao doc

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update chat_templating_multimodal.md

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* use full name for int8

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* revert int8 title

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
2025-06-30 07:56:55 -07:00
Lysandre Debut
e8f90b5397
Split transformers chat and transformers serve (#38443)
* Next token

* Split chat and serve

* Support both generation methods

* Style

* Generation Config

* temp

* temp

* Finalize serving.py

Co-authored-by: =?UTF-8?q?c=C3=A9lina?= <hanouticelina@gmail.com>

* Finalize chat.py

* Update src/transformers/commands/serving.py

Co-authored-by: célina <hanouticelina@gmail.com>

* Lucain's comments

Co-authored-by: Lucain <lucain@huggingface.co>

* Update

* Last comments on PR

* Better error handling

* Better error handling

* CI errors

* CI errors

* Add tests

* Fix tests

* Fix tests

* [chat] Split chat/serve (built on top of lysandre's PR) (#39031)

* Next token

* Split chat and serve

* Support both generation methods

* Style

* Generation Config

* temp

* temp

* Finalize serving.py

Co-authored-by: =?UTF-8?q?c=C3=A9lina?= <hanouticelina@gmail.com>

* Finalize chat.py

* Update src/transformers/commands/serving.py

Co-authored-by: célina <hanouticelina@gmail.com>

* Lucain's comments

Co-authored-by: Lucain <lucain@huggingface.co>

* Update

* Last comments on PR

* Better error handling

* Better error handling

* CI errors

* CI errors

* Add tests

* Fix tests

* Fix tests

* streaming tool call

* abstract tool state; set tool start as eos

* todos

* server working on models without tools

* rm chat's deprecated flags

* chat defaults

* kv cache persists across calls

* add server docs

* link

* Update src/transformers/commands/serving.py

* Apply suggestions from code review

* i love merge conflicts

* solve multi turn with tiny-agents

* On the fly switching of the models

* Remove required positional arg

---------

Co-authored-by: Lysandre <hi@lysand.re>
Co-authored-by: =?UTF-8?q?c=C3=A9lina?= <hanouticelina@gmail.com>
Co-authored-by: Lucain <lucain@huggingface.co>

* Protect names

* Fix tests

---------

Co-authored-by: =?UTF-8?q?c=C3=A9lina?= <hanouticelina@gmail.com>
Co-authored-by: Lucain <lucain@huggingface.co>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
2025-06-30 15:10:53 +02:00
Ryan Mullins
ed9f252608
docs: Gemma 3n audio encoder (#39087)
Updating Gemma 3n docs and docstrings to clarify the relationship
between the newly trained audio encoder used in Gemma 3n and the USM
model from the original paper.
2025-06-30 14:10:51 +02:00
Sandeep Yadav
18143c76bf
Sandeepyadav1478/2025 06 19 deberta v2 model card update (#38895)
* [docs]: update deberta-v2.md model card

* chore: req updates

* chore: address code review feedback and update docs

* chore: review feedback and updates

* chore: model selection updates

* chores: quantizations review updates
2025-06-27 10:35:30 -07:00
farrosalferro
dd7dc4a4a2
Add Fast Image Processor for Chameleon (#37140)
* Add Fast Image Processor for Chameleon

* add warning to resize and move blend_rgba to convert_to_rgb

* Remove unrelated files

* Update image_processing_chameleon_fast to use auto_docstring

* fix equivalence test

---------

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
2025-06-27 15:26:57 +00:00
MinJu-Ha
49d9fd49bd
Add Fast Image Processor for mobileViT (#37143)
* Add image_processing_mobilevit_fast.py

* Fix copies

* update _preprocess for channel_flip

* Update for batched image processing

* Resolve merge conflicts with main

* Fix import order and remove trailing whitespace (ruff clean-up)

* Fix copy inconsistencies

* Add NotImplementedError for post_process_semantic_segmentation to satisfy repo checks

* Add auto_docstring

* Adjust style

* Update docs/source/en/model_doc/mobilevit.md

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Update src/transformers/models/mobilevit/image_processing_mobilevit_fast.py

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Update src/transformers/models/mobilevit/image_processing_mobilevit_fast.py

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Delete not used function

* test: add missing tests for  and

* Add post_process_semantic_segmentation to mobilevit_fast.py

* Add preprocess function to image_processing_mobilebit_fast.py

* ruff check for formatting

* fix: modify preprocess method to handle BatchFeature correctly

* Remove logic for default value assignment

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Remove normalization adn RGB conversion logic not used in slow processor

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Simplify return_tensors logic using one-liner conditional expression

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* Remove unused normalization and format parameters

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>

* add **kwargs and remove default values in _preprocess

* add slow_fast equivalence tests for segmentation

* style: autoformat code with ruff

* Fix slow_fast equivalence test

* merge + remove skipped test

---------

Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
2025-06-27 14:40:24 +00:00
Nahieli
4336ecd1ea
add fast image processor nougat (#37661)
* add fast image processor nougat

* test fixes

* docstring white space

* last fixes

* docstring_type

* tolerance unit test

* fix tolerance

* fix rtol

* remove traling white space

* remove white space

* note for tolerance unit test

* fix tests

* remove print

---------

Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
2025-06-27 14:39:43 +00:00
Yaswanth Gali
1750c518dd
Add EoMT Model || 🚨 Fix Mask2Former loss calculation (#37610)
* Initial Commit

* up

* More changes

* up

* Only mask_logits mismatch

* close enough logits debug later

* fixes

* format

* Add dummy loss

* Close enough processing for semantic seg

* nit

* Added panoptic postprocessor

* refactor

* refactor

* finally fixed panoptic postprocessor

* temp update

* Refactor ForUniversalSegmentation class

* nits and config update

* Few fixes and inference matches

* change mapping

* Added training support but loss slightly off 🥲

* Loss is matching 😀

* update

* Initial tests skelton

* changes

* tests update

* more modular

* initial tests

* updates

* better docstrings

* changes

* proc tests passing :)

* Image processor update

* tiny change

* QOL changes

* Update test w.r.t latest attn refactor

* repo-consistency fixes

* up

* Image proc fix and integration tests :)

* docs update

* integration tests

* fix

* docs update 🥰

* minor fix

* Happy CI

* fix

* obvious refactoring

* refactoring w.r.t review

* Add fask image proc skelton

* Fast Image proc and cleanups

* Use more modular

* tests update

* Add more tests

* Nit

* QOL updates

* change init_weights to torch default

* add eager func coz of make style

* up

* changes

* typo fix

* Updates

* More deterministic tests

* More modular

* go more modular 🚀

* up

* dump

* add supprot for giant ckpts

* overhaul

* modular

* refactor

* instace seg is ready

* cleanup

* forgot this

* docs cleanup

* minor changes

* EoMT - > Eomt

* Happy CI

* remove redundant comment

* Change model references

* final change

* check annealing per block

* My other PR changes 😂

---------

Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
2025-06-27 14:18:18 +02:00
Steven Liu
a52478253b
[docs] Tensor parallelism (#38241)
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* updates

* feedback

* badges

* fix?

* fix?

* fix?

* fix?
2025-06-26 14:40:45 -07:00
Steven Liu
84e8696cae
[docs] @auto_docstring (#39011)
* refactor

* feedback
2025-06-26 14:21:54 -07:00
Drew Ross
018855de63
Update PEGASUS-X model card (#38971)
* Update PEGASUS-X model card

* Add cache_implementation argument in quantization code example

* Update CLI example

* Apply suggestions from code review

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Remove TensorFlow and Flax badges

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-26 13:54:48 -07:00
Steven Liu
757c26fb40
[docs] Model contribution (#38995)
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improve
2025-06-26 12:25:14 -07:00
StevenBucaille
f171e7e884
Update SuperPoint model card (#38896)
* docs: first draft to more standard SuperPoint documentation

* Apply suggestions from code review

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* docs: reverted changes on Auto classes

* docs: addressed the rest of the comments

* docs: remove outdated reference to keypoint detection task guide in SuperPoint documentation

* Update superpoint.md

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-26 10:13:06 -07:00
Ryan Mullins
c63cfd6a83
Gemma 3n (#39059)
* Gemma 3n

* initial commit of Gemma 3n scaffold

* Fixing param pass through on Gemm3p5RMSNorm

* Adds Einsum layer to Gemma 3n

* Updating EinsumLayer API

* Undoing erroneous force push

* Reverting RMSNorm to with_scale by default

* Adds LAuReL to Gemma 3n

* Adds AltUp to Gemma 3n

* Adding Gemma3p5 overall and text config with vision and audio config placeholders (#3)

* Adding gemma3p5 text configs

* Adding audio config placeholders

* Adding a placeholder for vision configs

* Updating MobileNetVisionConfig, inheriting TimmWrapperConfig

* Updating text configs

* Update src/transformers/models/gemma3p5/modular_gemma3p5.py

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Removing altup configs to accept the suggested configs

* Update src/transformers/models/gemma3p5/modular_gemma3p5.py

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating altup config

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Addressing review comments and updating text configs

* Adding a config for activation sparsity

* Updating configs to pass through options to super class init and adjust some name prefixes

* Updating laurel and altup with corrected config values

* Normalizing sub_config initializers

---------

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating MLP with activation sparsity (#2)

* Updating DecoderBlock for Gemma 3n (#3)

* Initial Gemm3nTextModel (#4)

NOTE: This implementation WILL CHANGE in the coming weeks, however, changes will be strictly additive and this will remain a suitable baseline for downstream implementations to reference.

* Adding KV Cache Sharing

* Adds Einsum layer to Gemma 3n

* Updating EinsumLayer API

* Refactored kv cache sharing in attention

* Adding KVStore for cache sharing

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update src/transformers/cache_utils.py

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Undoing erroneous force push

* Reverting RMSNorm to with_scale by default

* Adds LAuReL to Gemma 3n

* Updating KV Cache Sharing implementation

* Updating the q and k norm definitions in the attention module

* Fixing name error for q,k,v RMS norm to use the right 3n module

* Updating MLP with activation sparsity

* Updating DecoderBlock for Gemma 3.5

* Updating kv cache sharing implementation with the use of a cache buffer and refactoring some lines of code

* Isolating KV Cache logic to relevant components

* Fixing logic error in Gemma3nAttention.forward

* Refactoring caching contributions and fixing kv_store initialization

* Simplifying Configs

* Remove errant self from super init call

* Bug fix in the Attention module - changing self.head_dim to config.head_dim

* Bug fixes in the LaurelBlock and RMS Norm super init call

* removing redundant code from a merge

* Adding per_layer_inputs to TextModel

* Adding preprocess embeddings with altup

* Adds per-layer-to-single output and a host of TODOs

* Integrating altup predict with the model workflow and other minor bug fixes

* Using nn.Embedding temporarily for text model

* It goes forward

* Minor refactor of attention sparsity and RoPE initialization

* Fixing duplicate rope_scaling param bug when loading from pretrained

---------

Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>

* Normalizing on altup_num_inputs config option

* regenerating modeling file after syncing to HEAD

* Use torch.std(..., unbiased=False) for activation sparsity (#8)

* Refactoring to a single QVK Norm (#13)

* AltUp: support scale_corrected_output (#14)

* Converts einsums to nn.Linear (#7)

* Converts einsums to nn.Linear

* Removing unused variables

* Aligning SharedKVCache with HybridCache (#11)

* Alinging SharedKVStore with HybridCache

* Remove KVStore. Refactor apply_rotary_pos_emb for sharing

* Addressing review comments

* Supporting split modality embeddings in Gemma3n (#10)

* Adding the Embedder class

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Addressing review comments, adding audio embedding layers, integrating embedder with the remaining architecture, adding a forward method for conditional generation

* Apply suggestions from code review

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Update modular

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>

* Addressing review comments, prop drilling audio and vision configs to the text config

* Removing TODO's that have been addressed

* Simplify Embedder init and add audio embeddings

* Embeddings refactor. Adds Gemma3nAudioEmbedder and Gemma3nVisionEmbedder

* Refactoring vision and audio embeddings into ConditionalGeneration model

---------

Co-authored-by: Ryan Mullins <ryan@ryanmullins.org>
Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating attention mask for Gemma 3.5 (#15)

* xxx_token_index to xxx_token_id

* remvoing deprecated last_cache_position

* Removing references to SigLIP

* Always init per-layer inputs

* Using torch.finfo().min for epsilon_tensor

* Gemma3nDecoderLayer inherits from Gemma3DecoderLayer. Remove gating lambdas

* fix modular GEMMA3N_INPUTS_DOCSTRING

* Gemma3nAttention inherits from Gemma3Attention

* Modular inheritance fixes

* CausalLM conversion script for 4B model (#16)

* Add Gemma3n Audio Encoder (#6)

* initial commit of Gemma 3.5 scaffold

* Fixing param pass through on Gemm3nRMSNorm

* Adds Einsum layer to Gemma 3.5

* Updating EinsumLayer API

* Undoing erroneous force push

* Reverting RMSNorm to with_scale by default

* Adds LAuReL to Gemma 3n

* Adds AltUp to Gemma 3n

* Adding Gemma3n overall and text config with vision and audio config placeholders (#3)

* Adding gemma3n text configs

* Adding audio config placeholders

* Adding a placeholder for vision configs

* Updating MobileNetVisionConfig, inheriting TimmWrapperConfig

* Updating text configs

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Removing altup configs to accept the suggested configs

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating altup config

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Addressing review comments and updating text configs

* Adding a config for activation sparsity

* Updating configs to pass through options to super class init and adjust some name prefixes

* Updating laurel and altup with corrected config values

* Normalizing sub_config initializers

---------

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating MLP with activation sparsity (#2)

* Updating DecoderBlock for Gemma 3.5 (#3)

* Initial Gemm3nTextModel (#4)

NOTE: This implementation WILL CHANGE in the coming weeks, however, changes will be strictly additive and this will remain a suitable baseline for downstream implementations to reference.

* Adding KV Cache Sharing

* Adds Einsum layer to Gemma 3.5

* Updating EinsumLayer API

* Refactored kv cache sharing in attention

* Adding KVStore for cache sharing

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update src/transformers/cache_utils.py

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Undoing erroneous force push

* Reverting RMSNorm to with_scale by default

* Adds LAuReL to Gemma 3n

* Updating KV Cache Sharing implementation

* Updating the q and k norm definitions in the attention module

* Fixing name error for q,k,v RMS norm to use the right Gemma 3n module

* Updating MLP with activation sparsity

* Updating DecoderBlock for Gemma 3.5

* Updating kv cache sharing implementation with the use of a cache buffer and refactoring some lines of code

* Isolating KV Cache logic to relevant components

* Fixing logic error in Gemma3nAttention.forward

* Refactoring caching contributions and fixing kv_store initialization

* Simplifying Configs

* Remove errant self from super init call

* Bug fix in the Attention module - changing self.head_dim to config.head_dim

* Bug fixes in the LaurelBlock and RMS Norm super init call

* removing redundant code from a merge

* Adding per_layer_inputs to TextModel

* Adding preprocess embeddings with altup

* Adds per-layer-to-single output and a host of TODOs

* Integrating altup predict with the model workflow and other minor bug fixes

* Using nn.Embedding temporarily for text model

* It goes forward

* Minor refactor of attention sparsity and RoPE initialization

* Fixing duplicate rope_scaling param bug when loading from pretrained

---------

Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>

* Normalizing on altup_num_inputs config option

* Adding audio encoder config

* Adds high-level components for Audio Encoder

* Implement uniform reducer for Audio Encoder

* Adding placeholders for Conformer components in Audio Encoder

* Adding placeholders for SubSampleConvProjection components in Audio Encoder

* Adding SequenceLayer component placeholders

* Implementing Gemma3nAudioEncoder with nn.Sequential

* Implementing Gemma3nAudioSubSampleConvProjection with nn.Sequential

* Implementing Conformer model with SequenceLayers

* Use OrderedDict in nn.Sequential initializers

* Implements sl.Residual in Torch with nn.Sequential and OrderedDict

* Adopting a base SequenceLayer class with default forward() method

* Implementing sl.GatedLinearUnit in Torch

* Implementing sl.Swish in Torch

* Implementing sl.ReLU in Torch

* Implementing sl.Scale in Torch

* Removing sl.Dropout after tree-shaking

* Implementing sl.RMSNorm in Torch with fake shape

* Implementing sl.GroupNorm in Torch

* Implementing sl.Conv2d in Torch

* Implementing sl.Dense in Torch

* Removing sl.Delay layers, which act as pass-throughs

* Connecting shapes to configs in initializers

* Removing sl.Emit

* Implementing sl.ExpandDims in Torch

* Adding sl.GradientClipping to Torch

* Implementing sl.DenseShaped in Torch

* Implementing sl.LDPA in Torch

* Removing unused sl.CombinedQKVProj class

* Fixing erroneous type hint

* Implemnenting sl.DepthwiseConv1D in Torch

* Implementing sl.MaskInvalid in Torch

* Fixes for initialization

* Fixes for saving weights

* Removing einsums per feedback from HF staff

* Removing Sequence Layers idioms from audio encoder

* Fixes for reviewer comments

* CausalLM conversion script for 4B model

* inv_timescales to non-persistent buffer

* Addressing audio encoder Attention feedback

* Addressing Gemma3nAudioSSCPConvBlock feedback

* Addressing Gemma3nAudioConformerAttention feedback

* Addressing padding feedback

* Weights conversion loads audio state dict

* Always use vision_config so saving works

* Token id updates for configs

* Stubs for interleaving audio embs

* Addressing reviewer feedback

---------

Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>
Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>

* Fixing cache access error

* Removing duplicate code from a bad merge

* Gemma 3n Text + Vision Part 1 (#17)

* testing utilities for numerics comparisons

* Corrected einsum to nn.Linear weights conversion

* Inherit scaled word embs from Gemma3 not Bart

* Fixing transposes for collapsed linears

* More transpose fixes

* numpy api fix

* RMSNorm: Explicit kwargs, scale_shift=0.0 when with_scale=True

* Force AltUp  to float32

* Updating debugging script for AudioEncoder debugging

* Support divide_weight_by_sqrt_fan_in from JAX for per-layer inputs

* Correcting attention einsum conversions

* RMSNorm in type of x

* Fixing douplicate laurel norm/gating

* KV sharing using the right previous indices

* Refactor kv shared index computation. Correct frac_shared_layers

* Use num_shared_layers instead of inferring from a fraction

* fixing a bug for logging

* Fix shared data_ptrs in altup inits

* rope: adjust proj -> norm -> rope to preserve computation (#20)

* rope: adjust proj -> norm -> rope to preserve computation

* Removing some breaking language model fluff in ConditionalGeneration

* Consolidate query_states transforms

---------

Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>
Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Vectorize the loops in AltUp (#19)

* Vectorize the loops in AltUp

* fix typo

* Expanding to support batched inputs

* remove extra debug script

* Fix AltUp.forward

---------

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Add 'scale_shift=0.0, with_scale=True' to the final norm in TextModel

* Convert norm to 1/sqrt (#21)

* Convert norm to 1/sqrt

* Scale shift change per Phil's rec

* Adding default activation sparsity

* Fixing 2B config in weights conversion script

* Fixing RMSNorm parameters - adding scale_shift and with_scale

* Correcting query pre-attention scaling

* Adding query_rescale_scalar to text config

* Adding layer_idx to MLP

* Permafix for input_layernorm

* Use 1/sqrt instead of rsqrt in DecoderLayer

* Fix o_proj conversion

* Conversion script update for vision encoder

* Removing logging for debugging timm model

* Fixing bugs in Gemma3nForConditionalGeneration for text generation

* Generating the modeling_gemma3n.py file

* Removing the addition of an erroneous line in the modeling file

* Adding gemma3n text model to modeling_auto

* Bugfix: Updating the interleaving of inputs_embeds and vision_embeds

* Updating the modeling file with the latest bugfix changes

* Updating models/auto for Gemma 3n

* using AutoTokenizer in forward test

* Adding processing_gemma3n.py

* Gemma 3n configured for AutoModel. Conversion script updated.

* Removing errant merge artifacts

---------

Co-authored-by: Mayank Chaturvedi <imayank@google.com>
Co-authored-by: Douglas Reid <douglas-reid@users.noreply.github.com>
Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>

* Removing errant debugging statements from Gemma 3

* Gemma3n audio model (#18)

* testing utilities for numerics comparisons

* Implement CumulativeGroupNorm and add to SubSampleConvProjection and SSCPConvBlock

* Add audio version of forward script based on RyanMullins' implementation

* Updating to match encoder tests. WIP: config question needs resolving

* Updates to audio classes to enable end-to-end running

* Removing vestigial classes, cleaning up print statements

* Adding SiLU / Swish to audio conformer feed forward block

* Shifted Gemma3p5Audio naming prefix to Gemma3NanoAudio

* Adding outputs to audio test

* Fixes to padding in SSCP and 1D convolution, align RMS Norm with wider model

* Update forward test to load from local weights

* Update conversion to process / output audio layers

* Update __all__ to export audio encoder

* AutoModel registration for Gemma 3n Audio

* Use AutoModel for ConditionalGeneration.audio_tower

* Fixing input_proj_linear transpose

* Fixing Gemma3NanoAudioConformerAttention.post conversion

* Fixing Gemma3NanoAudioSSCPConvBlock.conv weights conversion

* Correcting indentation issue on Gemma3p5RMSNorm

---------

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Text + Vision Part 2 (#23)

* Updates for ConditionalGeneration.get_image_features

* Adding a WIP draft of image_processing_gemma3p5.py

* Update src/transformers/models/gemma3p5/modular_gemma3p5.py

Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>

* Modular conversion after github suggested change

* Text + image gives good results

* Fixing image size preset

* Updating configs for the 2B variant in the conversion script

* Using final generation config in conversion script

---------

Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>

* Audio Integration (#12)

* initial commit of Gemma 3n scaffold

* Fixing param pass through on Gemm3nRMSNorm

* Adds Einsum layer to Gemma 3n

* Updating EinsumLayer API

* Undoing erroneous force push

* Reverting RMSNorm to with_scale by default

* Adds LAuReL to Gemma 3n

* Adds AltUp to Gemma 3n

* Adding Gemma 3n overall and text config with vision and audio config placeholders (#3)

* Adding Gemma 3n text configs

* Adding audio config placeholders

* Adding a placeholder for vision configs

* Updating MobileNetVisionConfig, inheriting TimmWrapperConfig

* Updating text configs

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Removing altup configs to accept the suggested configs

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating altup config

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Addressing review comments and updating text configs

* Adding a config for activation sparsity

* Updating configs to pass through options to super class init and adjust some name prefixes

* Updating laurel and altup with corrected config values

* Normalizing sub_config initializers

---------

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Updating MLP with activation sparsity (#2)

* Updating DecoderBlock for Gemma 3n (#3)

* Initial Gemma3nTextModel (#4)

NOTE: This implementation WILL CHANGE in the coming weeks, however, changes will be strictly additive and this will remain a suitable baseline for downstream implementations to reference.

* Adding KV Cache Sharing

* Adds Einsum layer to Gemma 3n

* Updating EinsumLayer API

* Refactored kv cache sharing in attention

* Adding KVStore for cache sharing

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update modular

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Update src/transformers/cache_utils.py

Co-authored-by: Ryan Mullins <ryanmullins@google.com>

* Undoing erroneous force push

* Reverting RMSNorm to with_scale by default

* Adds LAuReL to Gemma 3n

* Updating KV Cache Sharing implementation

* Updating the q and k norm definitions in the attention module

* Fixing name error for q,k,v RMS norm to use the right 3n module

* Updating MLP with activation sparsity

* Updating DecoderBlock for Gemma 3n

* Updating kv cache sharing implementation with the use of a cache buffer and refactoring some lines of code

* Isolating KV Cache logic to relevant components

* Fixing logic error in Gemma3nAttention.forward

* Refactoring caching contributions and fixing kv_store initialization

* Simplifying Configs

* Remove errant self from super init call

* Bug fix in the Attention module - changing self.head_dim to config.head_dim

* Bug fixes in the LaurelBlock and RMS Norm super init call

* removing redundant code from a merge

* Adding per_layer_inputs to TextModel

* Adding preprocess embeddings with altup

* Adds per-layer-to-single output and a host of TODOs

* Integrating altup predict with the model workflow and other minor bug fixes

* Using nn.Embedding temporarily for text model

* It goes forward

* Minor refactor of attention sparsity and RoPE initialization

* Fixing duplicate rope_scaling param bug when loading from pretrained

---------

Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>

* Normalizing on altup_num_inputs config option

* Adding audio encoder config

* Adds high-level components for Audio Encoder

* Implement uniform reducer for Audio Encoder

* Adding placeholders for Conformer components in Audio Encoder

* Adding placeholders for SubSampleConvProjection components in Audio Encoder

* Adding SequenceLayer component placeholders

* Implementing Gemma3nAudioEncoder with nn.Sequential

* Implementing Gemma3nAudioSubSampleConvProjection with nn.Sequential

* Implementing Conformer model with SequenceLayers

* Use OrderedDict in nn.Sequential initializers

* Implements sl.Residual in Torch with nn.Sequential and OrderedDict

* Adopting a base SequenceLayer class with default forward() method

* Implementing sl.GatedLinearUnit in Torch

* Implementing sl.Swish in Torch

* Implementing sl.ReLU in Torch

* Implementing sl.Scale in Torch

* Removing sl.Dropout after tree-shaking

* Implementing sl.RMSNorm in Torch with fake shape

* Implementing sl.GroupNorm in Torch

* Implementing sl.Conv2d in Torch

* Implementing sl.Dense in Torch

* Removing sl.Delay layers, which act as pass-throughs

* Connecting shapes to configs in initializers

* Removing sl.Emit

* Implementing sl.ExpandDims in Torch

* Adding sl.GradientClipping to Torch

* Implementing sl.DenseShaped in Torch

* Implementing sl.LDPA in Torch

* Removing unused sl.CombinedQKVProj class

* Fixing erroneous type hint

* Implemnenting sl.DepthwiseConv1D in Torch

* Implementing sl.MaskInvalid in Torch

* Fixes for initialization

* Fixes for saving weights

* Removing einsums per feedback from HF staff

* Removing Sequence Layers idioms from audio encoder

* Fixes for reviewer comments

* Converting sl.Frontend to FeatureExtractor

* Updates for ConditionalGeneration.get_image_features

* Adding a WIP draft of image_processing_gemma3n.py

* Update modular

Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>

* Modular conversion after github suggested change

* Text + image gives good results

* Fixing image size preset

* Draft of audio data in chat template

* Removing image processing. Using SigLIP instead.

* Audio input going end-to-end

* Fixing dtype issues in audio encoder

* x-lib formatting consistency

* Adding example data

* Save preprocessor_config.json from conversion script

* Instrumentaiton for debugging

* Additional instrumentation for preprocessing debugging

* Updates to preprocessor, padding; produces correct end-to-end results on sample

* Tackling configuraiton TODOs

* Start of feature extractor refatcor

* Adds Numpy version of USM extractor, removes Torch version and dependencies

* Fixing AltUp.correct coef permute

* Supporting batches of single audio segment inputs

* Docstrings updates for config

* In-lining audio feature extraction

* Adjustments to conversion script and smoke test script

---------

Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>
Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: pculliton <phillipculliton@gmail.com>

* Gemma 3n renaming

* Removing test data and utilities

* Renaming test files

* Gemma 3n refactor

* Fix tokenizer config in conversion script

* Address reviewer feedback

* FeatureExtractor returns float32 by default

* Adding basic tests for audio, and input name for audio encoder

* Audio integration test, updates to model_id for other integration tests

* Use scales for q and k norms (#26)

* Update audio integration test to use HF dataset

* Reviewer feedback

* Expand embedding table to full vocab size in weights conversion

* Mix-n-match MatFormers for Gemma 3n (#25)

* Remove in-place operations (#30)

* chore: removing inplace ops

* remove [tensor] * n pattern

* chore: reviewer feedback in AudioEncoder and AltUp

* More grad clipping

* Dynamo compatibility

* fix: cache slicing error

* chore: simplify shared kv cache slicing

* chore: vision encoder rename in timm

* fix: image processor do_normalize=False

* fixup: style

* chore: model_doc

* fix: docs for code quality

* chore: repo consistency

* fix: RMSNorm in float as in prior Gemmas

* fix: per_layer_inputs = None

* chore: Gemma3nForCausalLM from Gemma3nForConditionalGeneration checkpoint

* chore: repo consistency

* Add initial unit tests for Gemma3nAudioFeatureExtractor (#27)

* Add initial unit tests for Gemma3nAudioFeatureExtractor

* Add basic unit tests for Gemma3nProcessor (#28)

Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>

* parameterize tests

---------

Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>

* chore: code style

* fix: test cases

* style and consistency

* fix config in the test to be coherent with layer cache sharing

* fix hidden states in tests and code

* inits and mappings

* fix modality prefixes

* test order and prefixes

* fix test exception

* fix class order and reduce model size for faster tests

* restore _checkpoint_conversion_mapping to load Caual from Conditional

* fix config mapping!

* fix: reviewer feedback

---------

Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>
Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: Mayank Chaturvedi <imayank@google.com>
Co-authored-by: Douglas Reid <douglas-reid@users.noreply.github.com>
Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
Co-authored-by: pculliton <phillipculliton@gmail.com>
Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>

* fix import test

* add model args

* auto_docstring

* replace test path

* consistency

* skip tests for now

* fix docstring for doc builder

* skip unused attr

---------

Co-authored-by: SindhuRaghuram97 <114270661+SindhuRaghuram97@users.noreply.github.com>
Co-authored-by: Sindhu Raghuram <sindhuraghuram@google.com>
Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: Mayank Chaturvedi <imayank@google.com>
Co-authored-by: Douglas Reid <douglas-reid@users.noreply.github.com>
Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
Co-authored-by: pculliton <phillipculliton@gmail.com>
Co-authored-by: Aritra Roy Gosthipaty <aritra.born2fly@gmail.com>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
Co-authored-by: Arthur <arthur.zucker@gmail.com>
2025-06-26 17:55:47 +02:00
Jaeyong Sung
583db52bc6
Add Dia model (#38405)
* add dia model

* add tokenizer files

* cleanup some stuff

* brut copy paste code

* rough cleanup of the modeling code

* nuke some stuff

* more nuking

* more cleanups

* updates

* add mulitLayerEmbedding vectorization

* nits

* more modeling simplifications

* updates

* update rope

* update rope

* just fixup

* update configuration files

* more cleanup!

* default config values

* update

* forgotten comma

* another comma!

* update, more cleanups

* just more nits

* more config cleanups

* time for the encoder

* fix

* sa=mall nit

* nits

* n

* refacto a bit

* cleanup

* update cv scipt

* fix last issues

* fix last nits

* styling

* small fixes

* just run 1 generation

* fixes

* nits

* fix conversion

* fix

* more fixes

* full generate

* ouf!

* fixes!

* updates

* fix

* fix cvrt

* fixup

* nits

* delete wrong test

* update

* update

* test tokenization

* let's start changing things bit by bit - fix encoder step

* removing custom generation, moving to GenerationMixin

* add encoder decoder attention masks for generation

* mask changes, correctness checked against ad29837 in dia repo

* refactor a bit already --> next cache

* too important not to push :)

* minimal cleanup + more todos

* make main overwrite modeling utils

* add cfg filter & eos filter

* add eos countdown & delay pattern

* update eos countdown

* add max step eos countdown

* fix tests

* fix some things

* fix generation with testing

* move cfg & eos stuff to logits processor

* make RepetitionPenaltyLogitsProcessor flexible

- can accept 3D scores like (batch_size, channel, vocab)

* fix input_ids concatenation dimension in GenerationMixin for flexibility

* Add DiaHangoverLogitsProcessor and DiaExponentialDecayLengthPenalty classes; refactor logits processing in DiaForConditionalGeneration to utilize new configurations and improve flexibility.

* Add stopping criteria

* refactor

* move delay pattern from processor to modeling like musicgen.

- add docs
- change eos countdown to eos delay pattern

* fix processor & fix tests

* refactor types

* refactor imports

* format code

* fix docstring to pass ci

* add docstring to DiaConfig & add DiaModel to test

* fix docstring

* add docstring

* fix some bugs

* check

* porting / merging results from other branch - IMPORTANT: it very likely breaks generation, the goal is to have a proper forward path first

* experimental testing of left padding for first channel

* whoops

* Fix merge to make generation work

* fix cfg filter

* add position ids

* add todos, break things

* revert changes to generation --> we will force 2d but go 3d on custom stuff

* refactor a lot, change prepare decoder ids to work with left padding (needs testing), add todos

* some first fixes to get to 10. in generation

* some more generation fixes / adjustment

* style + rope fixes

* move cfg out, simplify a few things, more todos

* nit

* start working on custom logit processors

* nit

* quick fixes

* cfg top k

* more refactor of logits processing, needs a decision if gen config gets the new attributes or if we move it to config or similar

* lets keep changes to core code minimal, only eos scaling is questionable atm

* simpler eos delay logits processor

* that was for debugging :D

* proof of concept rope

* small fix on device mismatch

* cfg fixes + delay logits max len

* transformers rope

* modular dia

* more cleanup

* keep modeling consistently 3D, generate handles 2D internally

* decoder starts with bos if nothing

* post processing prototype

* style

* lol

* force sample / greedy + fixes on padding

* style

* fixup tokenization

* nits

* revert

* start working on dia tests

* fix a lot of tests

* more test fixes

* nit

* more test fixes + some features to simplify code more

* more cleanup

* forgot that one

* autodocs

* small consistency fixes

* fix regression

* small fixes

* dia feature extraction

* docs

* wip processor

* fix processor order

* processing goes brrr

* transpose before

* small fix

* fix major bug but needs now a closer look into the custom processors esp cfg

* small thing on logits

* nits

* simplify indices and shifts

* add simpler version of padding tests back (temporarily)

* add logit processor tests

* starting tests on processor

* fix mask application during generation

* some fixes on the weights conversion

* style + fixup logits order

* simplify conversion

* nit

* remove padding tests

* nits on modeling

* hmm

* fix tests

* trigger

* probably gonna be reverted, just a quick design around audio tokenizer

* fixup typing

* post merge + more typing

* initial design for audio tokenizer

* more design changes

* nit

* more processor tests and style related things

* add to init

* protect import

* not sure why tbh

* add another protect

* more fixes

* wow

* it aint stopping :D

* another missed type issue

* ...

* change design around audio tokenizer to prioritize init and go for auto - in regards to the review

* change to new causal mask function + docstrings

* change ternary

* docs

* remove todo, i dont think its essential tbh

* remove pipeline as current pipelines do not fit in the current scheme, same as csm

* closer to wrapping up the processor

* text to audio, just for demo purposes (will likely be reverted)

* check if it's this

* save audio function

* ensure no grad

* fixes on prefixed audio, hop length is used via preprocess dac, device fixes

* integration tests (tested locally on a100) + some processor utils / fixes

* style

* nits

* another round of smaller things

* docs + some fixes (generate one might be big)

* msytery solved

* small fix on conversion

* add abstract audio tokenizer, change init check to abstract class

* nits

* update docs + fix some processing :D

* change inheritance scheme for audio tokenizer

* delete dead / unnecessary code in copied generate loop

* last nits on new pipeline behavior (+ todo on tests) + style

* trigger

---------

Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Vasqu <antonprogamer@gmail.com>
2025-06-26 11:04:23 +00:00
Joao Gante
1d45d90e5d
[tests] remove TF tests (uses of require_tf) (#38944)
Some checks are pending
Self-hosted runner (benchmark) / Benchmark (aws-g5-4xlarge-cache) (push) Waiting to run
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Update Transformers metadata / build_and_package (push) Waiting to run
* remove uses of require_tf

* remove redundant import guards

* this class has no tests

* nits

* del tf rng comment
2025-06-25 17:29:10 +00:00
eustlb
551e48f182
[Kyutai-STT] correct model type + model id (#39035)
* correct model type + model id

* udpate doc

* init fix

* style !!!
2025-06-25 16:09:00 +00:00
Anton Lozhkov
dad0e87c79
Add SmolLM3 (#38755)
* init smollm3

* integration tests

* config quirks

* docs stub

* rests round 2

* tests round 3

* tests round 4

* bring SWA back

* config checker pls

* final checkpoint

* style and copies

* Update src/transformers/models/smollm3/modular_smollm3.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/smollm3/modular_smollm3.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
2025-06-25 15:12:15 +00:00
Marcel Ambo Ndowah
3c1d4dfbac
Fix grammatical error in models documentation (#39019) 2025-06-25 14:55:22 +00:00
Quentin Lhoest
858f9b71a8
Remove script datasets in tests (#38940)
* remove trust_remote_code

* again

* Revert "Skip some tests for now (#38931)"

This reverts commit 31d30b7224.

* again

* style

* again

* again

* style

* fix integration test

* fix tests

* style

* fix

* fix

* fix the last ones

* style

* last one

* fix last

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
2025-06-25 14:31:20 +00:00
redmoe-moutain
7503cb9113
[Model] add dots1 (#38143)
* add dots1

* address comments

* fix

* add link to dots1 doc

* format

---------

Co-authored-by: taishan <rgtjf1@163.com>
2025-06-25 11:38:25 +02:00
Biao Zhang
3ef8896906
Encoder-Decoder Gemma (#38332)
* Initial submit

* Fix bugs:
1. add __init__ file
2. tied word embedding
3. support flash/flex attention
4. model saving and loading

* Code refactor:
* Rename encdecgemma to t5gemma.
* Split attention into self- and cross-attention
* Split stack into encoder and decoder
* Add test cases
* Add auto configuration

* Update configurations.

* Fix bugs related to copy and attribute checks

* Fix type union

* Fix merge errors

* run ruff format

* Run make style and update tests.

* Add t5gemma model doc.

* ruff and style formatting.

* Add missed module config.

* Add dummy checkpoint link to pass tests (need updated when real checkpoints are uplioaded.).

* Update model doc.

* Minor updates following Arthur's comments:
* replace docstrings with auto_docstrings
* remove checkpoint layers
* remove deprecate_kwargs

* fix rebase errors

* Fix docstring issues.

* fix t5gemma doc issue.

* run ruff format

* Updates:
* split encoder-only model out
* make t5gemmamodel encoder-decoder only
* update token and sequence classification
* update tests
2025-06-25 09:05:10 +00:00
Yuxuan Zhang
af9870265e
GLM-4.1V Model support (#38431)
* 20250508 Model Architecture

* Update modeling_glm4v.py

* Update modeling_glm4v.py

* Update modeling_glm4v.py

* update 1447

* 0526

* update

* format

* problem

* update

* update with only image embed diff

* Final

* upload

* update

* 1

* upload with ruff

* update

* update

* work

* 1

* 1

* update with new note

* 2

* Update convert_glm4v_mgt_weights_to_hf.py

* Update tokenization_auto.py

* update with new format

* remove rmsnrom

* draft with videos

* draft

* update

* update

* fix for review problem

* try to remove min_pixel

* update

* for test

* remove timestamps

* remove item

* update with remove

* change

* update 2200

* update

* Delete app.py

* format

* update

* Update test_video_processing_glm4v.py

* 1

* 2

* use new name

* Update test_video_processing_glm4v.py

* remove docs

* change

* update for image processors update

* 2108

* 2128

* Update modular_glm4v.py

* 1

* update some

* update

* rename

* 1

* remove tests output

* 2

* add configuration

* update

* Update test_video_processing_glm4v.py

* fix simple forward tests

* update with modular

* 1

* fix more tests

* fix generation test

* fix beam search and init

* modular changed

* fix beam search in case of single-image/video. Fails if multiple visuals per text

* update processor

* update test

* pass

* fix beam search

* update

* param correct

* Update convert_glm4v_mgt_weights_to_hf.py

* 1

* Update test_modeling_glm4v.py

* 4

* 2

* 2123 video process

* 2

* revert

* 1

* 2

* revert processing

* update preprocesor

* changed

* 1

* update

* update

* 6

* update

* update

* update

* Delete tmp.txt

* config

* Update video_processing_glm4v.py

* apply modular correctly

* move functions

* fix order

* update the longest_edge

* style

* simplify a lot

* fix random order of classes

* skip integration tests

* correctly fix the tests

* fix TP plan

---------

Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com>
2025-06-25 10:43:05 +02:00
Marcel Ambo Ndowah
48b6ef0238
Add Hugging Face authentication procedure for IDEs (PyCharm, VS Code,… (#38954)
* Add Hugging Face authentication procedure for IDEs (PyCharm, VS Code, etc.)

* Update quicktour.md

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-24 11:48:15 -07:00
eustlb
6bdd4ec952
Add kyutai stt (#38909)
* first draft

* cleaner version

* udpate tests + modeling

* add tests

* init

* udpate test_modeling_common

* fix tests

* csm Processor draft

* convertion update

* mimi cache padding convolutions draft

* mimi streaming udpates

* update mimi padding cache test

* udpate cache padding mimi test

* make style mimi

* updates generate moshi asr

* moshi asr integration tests (single + batched)

* update tests

* update conversion script

* good default sliding window value

* udpdate generate

* update test checkpoint

* nit

* fix mimi

* fix codec prefix

* revert

* revert

* update config

* update config

* unnecessary mimi input restriction

* remove delay in tokens

* remove _prepare_4d_causal_attention_mask_with_cache_position and _update_causal_mask

* test update

* modular update

* make style

* nit

* rename

* create codec model generation config at init

* remove delay

* max_new_tokens/length warning

* correct conv1 padding cache import for modular

* nit

* fix on encoder_past_key_values

* convert modular

* move frame_size to config

* move frame_size to config

* update test name

* handle first token is bos

* better handling of max_new_tokens

* fix

* fix batch size in test input prep

* update docstring

* convert modular

* make style

* make style

* add feature extractor

* correct modular convention name for feature_extraction file

* update convertion script

* doc processor

* update doc

* udpate init

* update model type

* fixes

* update tests

* fix

* make

* add doc

* nit

* fix

* doc

* auto mappings

* doc

* nit

* convert modular

* doc

* nit

* extend _keep_in_fp32_modules to enforce fp32

* renaming to stt

* doc update + test update

* doc fixes

* doc fix

* doc fix

* fix musicgen tests

* fix musicgen tests

* make style

* fix musicgen tests

* correct frame_rate config param for mimi

* update mimi test

* revert update mimi test

* enforce cpu test

* move cache init in cache class

* convert modular

* docstring update

* update model id

* feature_extractor -> feature_extraction (SEW)

* convert modular

* update model id
2025-06-24 18:01:15 +02:00
Crystalcareai
71de20b818
Add Arcee model support (#38621)
* Add Arcee model support to transformers

- Add ArceeConfig and model mappings for all task types (CausalLM, SequenceClassification, QuestionAnswering, TokenClassification)
- Add auto-loading support through AutoModel, AutoConfig, and AutoTokenizer
- Use LlamaTokenizer for tokenization
- Add FX graph support for Arcee models
- Create lazy loading module structure for Arcee

* feat: update YARN scaling and RoPE validation for Arcee model

* feat: add auto_docstring checkpoint config to Arcee model classes

* docs: add pre-trained model weights reference to Arcee configuration files

* refactor: move RoPE utilities to dedicated modeling_rope_utils module

* Add comprehensive test suite for Arcee model

- Add test_modeling_arcee.py following standard transformers test patterns
- Include tests for all model variants (CausalLM, SequenceClassification, QuestionAnswering, TokenClassification)
- Add specific test for ReLU² activation in ArceeMLP
- Add RoPE scaling tests including YARN support
- Follow CausalLMModelTest pattern used by similar models

* Add documentation for Arcee model

- Add comprehensive model documentation with usage examples
- Include all model variants in autodoc
- Add to table of contents in proper alphabetical order
- Fixes documentation coverage for Arcee model classes

* Make style/fixup

* fix copyright year

* Sync modular conversion

* revert in legacy supported models in src/transformers/utils/fx

* cleaned redundant code in modular_arcee.py

* cleaned testing

* removed pretraining tp

* fix styles

* integration testing

---------

Co-authored-by: Pranav <veldurthipranav@gmail.com>
Co-authored-by: Pranav <56645758+pranav4501@users.noreply.github.com>
2025-06-24 15:05:29 +02:00
casinca
21cb353b7b
[docs] Typos - Single GPU efficient training features (#38964)
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* Typos

- corrected bf16 training argument
- corrected header for SDPA

* improved readability for SDPA suggested by @stevhliu

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-23 12:33:10 -07:00
Yoni Gozlan
d29482cc91
Add Idefics2/3 and SmolVLM Fast image processors + improvements for fast image processors (#38157)
* add working idefics2 fast and improvements for fast nested images processing

* add fast image processors idefics 3 and smolvlm

* cleanup tests

* fic doc idefics2

* PR review and fix issues after merge

* Force providing disable_grouping to group_images_by_shape

* simplify group_images_by_shape

* fix modular

* Fix nits after review
2025-06-23 14:17:25 +00:00
Cyril Vallez
74f5e4a1fa
[modular] CLI allows positional arguments, and more defaults names for the optional arg (#38979)
* More defaults

* Update modular_model_converter.py
2025-06-23 12:40:01 +02:00
DongKyu Kang
2166b6b4ff
Update blip model card (#38513)
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* Update docs/source/en/model_doc/blip.md

* fix(docs/source/en/model_doc/blip.md): fix redundent typo error

* fix (docs/source/en/model_doc/blip.md): modify of review contents

* fix(docs/source/en/model_doc/blip.md): modify code block

* Update blip.md

---------

Co-authored-by: devkade <mouseku@moana-master>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-20 13:46:19 -07:00
Manuel de Prada Corral
166e823f77
Fix custom generate from local directory (#38916)
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Fix custom generate from local directory:
1. Create parent dirs before copying files (custom_generate dir)
2. Correctly copy relative imports to the submodule file.
3. Update docs.
2025-06-20 17:36:57 +01:00
Hamza Benchekroun
797860c68c
feat: add flexible Liger Kernel configuration to TrainingArguments (#38911)
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* feat: add flexible Liger Kernel configuration to TrainingArguments

Add support for granular Liger Kernel configuration through a new
`liger_kernel_config` parameter in TrainingArguments. This allows users
to selectively enable/disable specific kernels (rope, swiglu, cross_entropy,
etc.) instead of the current approach that rely on default configuration.

Features:
- Add `liger_kernel_config` dict parameter to TrainingArguments
- Support selective kernel application for all supported models
- Maintain full backward compatibility with existing `use_liger_kernel` flag

Example usage:
```python
TrainingArguments(
    use_liger_kernel=True,
    liger_kernel_config={
        "rope": True,
        "swiglu": True,
        "cross_entropy": False,
        "fused_linear_cross_entropy": True
    }
)
Closes #38905

* Address comments and update Liger section in Trainer docs
2025-06-19 15:54:08 +00:00
Dhruv
458e0b376c
Update bamba model card (#38853)
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* Update bamba model card

* Update the doc for bamba

* Update docs/source/en/model_doc/bamba.md

Bamba paragraph

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

Bamba collection url

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

Update Padding-Free Training to Notes heading

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

update examples

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

Update additional info

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

consistent casing

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

simplify sentences

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Include pipeline and cli examples + fix formatting

* Apply suggestions from code review

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/bamba.md

update cli id

* Update quantization example

* Fix auto code formatter changes

* Update cli command + include BambaModel

* Update docs/source/en/model_doc/bamba.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-18 16:01:25 -07:00
Sam Rae
b922b22ec2
36978 | Fast image processor for DPT model (#37481)
* chore: ran codegen script

* test: test_image_processor_properties

* test: test_image_processor_from_dict_with_kwargs

* test: wip - test_padding

* test: test_padding

* test: test_keep_aspect_ratio

* wip

* test

* test: wip

* test: wip

* test: test_call_segmentation_maps, wip

* chore: tidy up

* test: test_call_segmentation_maps

* fix: test_save_load_fast_slow

* test: reduce labels

* chore: make fixup

* chore: rm comment

* chore: tidy

* chore remove comment

* refactor: no need to infer channel dimesnion

* refactor: encapsulate logic for preparing segmentation maps

* refactor: improve readability of segmentation_map preparation

* improvement: batched version of pad_image

* chore: fixup

* docs

* chore: make quality

* chore: remove unecessary comment

* fix: add SemanticSegmentationMixin

* feat: add post_process_depth_estimation to fast dpt image processor

* chore: fix formatting

* remove max_height, max_width

* fix: better way of processin segmentation maps
- copied from Beit Fast processor

* chore: formatting + remove TODO

* chore: fixup styles

* chore: remove unecessary line break

* chore: core review suggestion to remove autodocstring

* fix: add do_reduce_labels logic + refactor
- refactor preprocess logic to make it consistent with other processors
- add missing reduce labels logic

* refactor: remove deprecated mixin

* chore: fixup

* use modular for dpt + final nit changes

* fix style

---------

Co-authored-by: Samuel Rae <samuelrae@Samuels-Air.fritz.box>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
2025-06-18 17:33:29 +00:00
Ashu_kun
c27f628e98
Docs: Add custom fine-tuning tutorial to TrOCR model page (#38847)
* Update trocr.md

Docs: add community fine‑tuning notebook link to TrOCR page

* apply suggested changes from PR review

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/trocr.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-18 09:38:58 -07:00
Matt
508a704055
No more Tuple, List, Dict (#38797)
* No more Tuple, List, Dict

* make fixup

* More style fixes

* Docstring fixes with regex replacement

* Trigger tests

* Redo fixes after rebase

* Fix copies

* [test all]

* update

* [test all]

* update

* [test all]

* make style after rebase

* Patch the hf_argparser test

* Patch the hf_argparser test

* style fixes

* style fixes

* style fixes

* Fix docstrings in Cohere test

* [test all]

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
2025-06-17 19:37:18 +01:00
SohamPrabhu
a396f4324b
Update roc bert docs (#38835)
* Moved the sources to the right

* small Changes

* Some Changes to moonshine

* Added the install to pipline

* updated the monshine model card

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Updated Documentation According to changes

* Fixed the model with the commits

* Changes to the roc_bert

* Final Update to the branch

* Adds Quantizaiton to the model

* Finsihed Fixing the Roc_bert docs

* Fixed Moshi

* Fixed Problems

* Fixed Problems

* Fixed Problems

* Fixed Problems

* Fixed Problems

* Fixed Problems

* Added the install to pipline

* updated the monshine model card

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/moonshine.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Updated Documentation According to changes

* Fixed the model with the commits

* Fixed the problems

* Final Fix

* Final Fix

* Final Fix

* Update roc_bert.md

---------

Co-authored-by: Your Name <sohamprabhu@Mac.fios-router.home>
Co-authored-by: Your Name <sohamprabhu@Sohams-MacBook-Air.local>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-17 11:02:18 -07:00
Md. Muhaimin Rahman
3ae52cc312
Update CvT documentation with improved usage examples and additional … (#38731)
* Update CvT documentation with improved usage examples and additional notes

* initial update

* cvt

* Update docs/source/en/model_doc/cvt.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update cvt.md

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-17 10:30:03 -07:00
StevenBucaille
e5a9ce48f7
Add LightGlue model (#31718)
* init

* chore: various changes to LightGlue

* chore: various changes to LightGlue

* chore: various changes to LightGlue

* chore: various changes to LightGlue

* Fixed dynamo bug and image padding tests

* refactor: applied refactoring changes from SuperGlue's concat, batch and stack functions to LightGlue file

* tests: removed sdpa support and changed expected values

* chore: added some docs and refactoring

* chore: fixed copy to superpoint.image_processing_superpoint.convert_to_grayscale

* feat: adding batch implementation

* feat: added validation for preprocess and post process method to LightGlueImageProcessor

* chore: changed convert_lightglue_to_hf script to comply with new standard

* chore: changed lightglue test values to match new lightglue config pushed to hub

* chore: simplified convert_lightglue_to_hf conversion map

* feat: adding batching implementation

* chore: make style

* feat: added threshold to post_process_keypoint_matching method

* fix: added missing instructions that turns keypoints back to absolute coordinate before matching forward

* fix: added typehint and docs

* chore: make style

* [run-slow] lightglue

* fix: add matches different from -1 to compute valid matches in post_process_keypoint_matching

* tests: added CUDA proof tests similar to SuperGlue

* chore: various changes to modeling_lightglue.py

- Added "Copies from" statements for copied functions from modeling_superglue.py
- Added missing docstrings
- Removed unused functions or classes
- Removed unnecessary statements
- Added missing typehints
- Added comments to the main forward method

* chore: various changes to convert_lightglue_to_hf.py

- Added model saving
- Added model reloading

* chore: fixed imports in lightglue files

* [run-slow] lightglue

* chore: make style

* [run-slow] lightglue

* Apply suggestions from code review

Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* [run-slow] lightglue

* chore: Applied some suggestions from review

- Added missing typehints
- Refactor "cuda" to device variable
- Variable renaming
- LightGlue output order changed
- Make style

* fix: added missing grayscale argument in image processor in case use of SuperPoint keypoint detector

* fix: changed lightglue HF repo to lightglue_superpoint with grayscale default to True

* refactor: make keypoints `(batch_size, num_keypoints, keypoint_dim)` through forward and unsqueeze only before attention layer

* refactor: refactor do_layer_keypoint_pruning

* tests: added tests with no early stop and keypoint pruning

* refactor: various refactoring to modeling_lightglue.py

- Removed unused functions
- Renamed variables for consistency
- Added comments for clarity
- Set methods to private in LightGlueForKeypointMatching
- Replaced tensor initialization to list then concatenation
- Used more pythonic list comprehension for repetitive instructions

* refactor: added comments and renamed filter_matches to get_matches_from_scores

* tests: added copied from statement with superglue tests

* docs: added comment to prepare_keypoint_matching_output function in tests

* [run-slow] lightglue

* refactor: reordered _concat_early_stopped_outputs in LightGlue class

* [run-slow] lightglue

* docs: added lightglue.md model doc

* docs: added Optional typehint to LightGlueKeypointMatchingOutput

* chore: removed pad_images function

* chore: set do_grayscale default value to True in LightGlueImageProcessor

* Apply suggestions from code review

Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Apply suggestions from code review

Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* docs: added missing LightGlueConfig typehint in nn.Module __init__ methods

* docs: removed unnecessary code in docs

* docs: import SuperPointConfig only from a TYPE_CHECKING context

* chore: use PretrainedConfig arguments `num_hidden_layers` and `num_attention_heads` instead of `num_layers` and `num_heads`

* chore: added organization as arg in convert_lightglue_to_hf.py script

* refactor: set device variable

* chore: added "gelu" in LightGlueConfig as hidden_act parameter

* docs: added comments to reshape.flip.reshape instruction to perform cross attention

* refactor: used batched inference for keypoint detector forward pass

* fix: added fix for SDPA tests

* docs: fixed docstring for LightGlueImageProcessor

* [run-slow] lightglue

* refactor: removed unused line

* refactor: added missing arguments in LightGlueConfig init method

* docs: added missing LightGlueConfig typehint in init methods

* refactor: added checkpoint url as default variable to verify models output only if it is the default url

* fix: moved print message inside if statement

* fix: added log assignment r removal in convert script

* fix: got rid of confidence_thresholds as registered buffers

* refactor: applied suggestions from SuperGlue PR

* docs: changed copyright to 2025

* refactor: modular LightGlue

* fix: removed unnecessary import

* feat: added plot_keypoint_matching method to LightGlueImageProcessor with matplotlib soft dependency

* fix: added missing import error for matplotlib

* Updated convert script to push on ETH org

* fix: added missing licence

* fix: make fix-copies

* refactor: use cohere apply_rotary_pos_emb function

* fix: update model references to use ETH-CVG/lightglue_superpoint

* refactor: add and use intermediate_size attribute in config to inherit CLIPMLP for LightGlueMLP

* refactor: explicit variables instead of slicing

* refactor: use can_return_tuple decorator in LightGlue model

* fix: make fix-copies

* docs: Update model references in `lightglue.md` to use the correct pretrained model from ETH-CVG

* Refactor LightGlue configuration and processing classes

- Updated type hints for `keypoint_detector_config` in `LightGlueConfig` to use `SuperPointConfig` directly.
- Changed `size` parameter in `LightGlueImageProcessor` to be optional.
- Modified `position_embeddings` in `LightGlueAttention` and `LightGlueAttentionBlock` to be optional tuples.
- Cleaned up import statements across multiple files for better readability and consistency.

* refactor: Update LightGlue configuration to enforce eager attention implementation

- Added `attn_implementation="eager"` to `keypoint_detector_config` in `LightGlueConfig` and `LightGlueAttention` classes.
- Removed unnecessary logging related to attention implementation fallback.
- Cleaned up import statements for better readability.

* refactor: renamed message into attention_output

* fix: ensure device compatibility in LightGlueMatchAssignmentLayer descriptor normalization

- Updated the normalization of `m_descriptors` to use the correct device for the tensor, ensuring compatibility across different hardware setups.

* refactor: removed Conv layers from init_weights since LightGlue doesn't have any

* refactor: replace add_start_docstrings with auto_docstring in LightGlue models

- Updated LightGlue model classes to utilize the new auto_docstring utility for automatic documentation generation.
- Removed legacy docstring handling to streamline the code and improve maintainability.

* refactor: simplify LightGlue image processing tests by inheriting from SuperGlue

- Refactored `LightGlueImageProcessingTester` and `LightGlueImageProcessingTest` to inherit from their SuperGlue counterparts, reducing code duplication.
- Removed redundant methods and properties, streamlining the test setup and improving maintainability.

* test: forced eager attention implementation to LightGlue model tests

- Updated `LightGlueModelTester` to include `attn_implementation="eager"` in the model configuration.
- This change aligns the test setup with the recent updates in LightGlue configuration for eager attention.

* refactor: update LightGlue model references

* fix: import error

* test: enhance LightGlue image processing tests with setup method

- Added a setup method in `LightGlueImageProcessingTest` to initialize `LightGlueImageProcessingTester`.
- Included a docstring for `LightGlueImageProcessingTester` to clarify its purpose.

* refactor: added LightGlue image processing implementation to modular file

* refactor: moved attention blocks into the transformer layer

* fix: added missing import

* fix: added missing import in __all__ variable

* doc: added comment about enforcing eager attention because of SuperPoint

* refactor: added SuperPoint eager attention comment and moved functions to the closest they are used

---------

Co-authored-by: Steven Bucaille <steven.bucaille@buawei.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
2025-06-17 18:10:23 +02:00
Dhruv
e61160c5db
Remove merge conflict artifacts in Albert model doc (#38849)
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2025-06-16 14:21:18 -07:00
Vanshu
64e9b049d9
Updated aya_vision.md (#38749)
* Update aya_vision.md

* Suggested changes made to aya_vision.md

* Quantization Example added - aya_vision.md

* Polished - aya_vision.md

* Update aya_vision.md

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-16 10:46:30 -07:00
Drew Ross
18c7f32daa
Fix broken tag in Longformer model card (#38828) 2025-06-16 07:44:40 -07:00
VolodymyrBg
b44b04ee9a
Fix broken notebooks link in Italian training docs (#38834)
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2025-06-16 07:38:51 -07:00
SOUVIK CHAND [ZD]
d5d007a1a0
Updated Albert model Card (#37753)
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* Updated Albert model Card

* Update docs/source/en/model_doc/albert.md

added the quotes in <hfoption id="Pipeline">

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/albert.md

updated checkpoints

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/albert.md

changed !Tips description

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* Update docs/source/en/model_doc/albert.md

updated text

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* Update docs/source/en/model_doc/albert.md

updated transformer-cli implementation

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/albert.md

changed text

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/albert.md

removed repeated description

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update albert.md

removed lines

* Update albert.md

updated pipeline code

* Update albert.md

updated auto model code, removed quantization as model size is not large, removed the attention visualizer part

* Update docs/source/en/model_doc/albert.md

updated notes

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update albert.md

reduced a  repeating point in notes

* Update docs/source/en/model_doc/albert.md

updated transformer-CLI

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/model_doc/albert.md

removed extra notes

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-13 14:58:06 -07:00
Sunil Reddy
443aafd3d6
[docs] updated roberta model card (#38777)
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* updated roberta model card

* fixes suggested after reviewing

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2025-06-13 12:02:44 -07:00
Steven Liu
fdb5da59dd
[docs] Update docs moved to the course (#38800)
* update

* update

* update not_doctested.txt

* slow_documentation_tests.txt
2025-06-13 12:02:27 -07:00
Pavel Iakubovskii
9bec2654ed
Add V-JEPA for video classification model (#38788)
* adding model and conversion scripts

* add imports to test vjepa conversion

* fix imports and make conversion work

* fix computation for short side

* replace attention with library attention function

* cleanup more attention classes

* remove config overrides

* add test cases, fix some of the failing ones

* fix the model outputs

* fix outputs of the model per review

* fix too big model test case

* fix styling __init__.py

* fix initialization test

* remove all asserts per review

* update sorting unsorting logic as per feedback

* remove is_video per review

* remove another is_video segment

* remove unwanted stuff

* small fixes

* add docstrings for the model

* revert adding vjepa2 config here

* update styling

* add config docstrings (wip)

* fix dpr issue

* removed test failing issues

* update styles

* merge predictor configs into main config

* remove processing code, add video processor

* remove permute which is not necessary now

* fix styles

* updated vjepa2 to be in video_processing_auto

* update comment for preprocessing

* test integration test and fix the outputs

* update test values, change test to look at repeated frames for a given image

* add a simple video processing test

* refactoring pixel_values_videos and upload ckpts to original

* fix torch_fx test cases

* remove unused config

* add all config docstrings

* add more integration tests

* add basic doc

* revert unwanted styling changes

* working make fixup

* Fix model_type in config

* Add ForVideoClassification model

* update attention implementation to fit new hf standards

* fix the preprocessing logic, ensure it matches the original model

* remove use_rope logic, cleanup

* fix docstrings

* Further cleanup, update doc

* Fix model prefix

* fix get_vision_features

* VJEPA2Embeddings style refactor

* nit, style comment

* change modules default values

* Only `str` activation in config

* GradientCheckpointingLayer

* fixup

* fix conversion script

* Remove return_dict

* remove None return typehint

* Refactor VJEPA2Layer, remove use_SiLU

* Fix fx tests

* dpr -> drop_path_rates

* move *ModelOutput on top

* format docs bit

* update docs

* update docs

* update doc example

* remove prune_heads from model

* remove unused config params

* refactor embed signature

* Add vjepa to docs

* Fix config docstring

* attention head

* update defaults

* Update docs/source/en/model_doc/vjepa2.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/model_doc/vjepa2.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Fix import

* Min refactoring

* Update HUB_SOURCE and HUB_REPO in conversion script

* Add missing headers

* VJEPA -> V-JEPA in docs

* Add image to doc

* fix style

* fix init weights

* change checkpoint name in modeling tests

* Initial cls head setup

* remove rop attention from head (not needed)

* remove swigluffn - not needed

* Add siglip layer

* Replace with siglip layer

* Rename Siglip - VJEPA2

* remove unused modules

* remove siglip mlp

* nit

* remove MLP

* Refactor head cross attention

* refactor VJEPA2HeadCrossAttentionLayer

* nit renaming

* fixup

* remove commented code

* Add cls head params to config

* depth from config

* move pooler + classifier  to the model

* Update for cls model signature

* move layers, rename a bit

* fix docs

* update weights init

* remove typehint for init

* add to auto-mapping

* enable tests

* Add conversion script

* fixup

* add to docs

* fix docs

* nit

* refactor for mapping

* clean

* Add integration test

* Fixing multi gpu test

* update not-split-modules

* update video cls test tolerance

* Increase test_inference_image tolerance

* Update no-split modules for multi gpu

* Apply suggestions from code review

* fixing multi-gpu

* fix docstring

* Add cls snippet to docs

* Update checkpoint
2025-06-13 17:56:15 +01:00
Prashant Tandon
93445aed06
change fsdp_strategy to fsdp in TrainingArguments in accelerate doc (#38807) 2025-06-13 15:32:40 +00:00