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.
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.
TST Fix PEFT integration test bitsandbytes config
The PEFT integration tests still used load_in_{4,8}_bit, which is
deprecated, moving to properly setting BitsAndBytesConfig. For 4bit,
also ensure that nf4 is being used to prevent
> RuntimeError: quant_type must be nf4 on CPU, got fp4
* 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>
* 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>
Some PEFT integration tests involving text generation pipelines were
failing since #38129 because the base model is too small to generate
longer sequences. Setting max_new_tokens fixes this.
* timestamp token is end of token time !!!
* ensure correct alignment between tokens and timestamp tokens
* ignore input tokens for DTW computation
* use num_frames to avoid token timestamp hallucinations
* token timestamps test updates !
* num_frames: deprecate and use attention_mask instead
* avoid breaking change
* fix the pipeline usage for chunk approach
* make style
* better logging
* better logging
* make style
* update tests with correct values
* fix a bunch of XPU UT failures on stock PyTorch 2.7 and 2.8
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* qwen3
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* quanto
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* models
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* idefics2
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* 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>
* 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>
* remove compile on mask creation, ensure kv blocks do not explode on indices
* trigger ci
* switch dynamic compilation to false
* patch new masking functions as well
* add len check
* i was wrong
* last comment
* 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
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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
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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
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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
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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>
* rm tf/flax tests
* more flax deletions
* revert fixture change
* reverted test that should not be deleted; rm tf/flax test
* revert
* fix a few add-model-like tests
* fix add-model-like checkpoint source
* a few more
* test_get_model_files_only_pt fix
* fix test_retrieve_info_for_model_with_xxx
* fix test_retrieve_model_classes
* relative paths are the devil
* add todo
* handle long form generation
* add warning
* correct incorrect in place token change
* update test to catch edge case
* make style
* update warning
* add doc
