* Trainer - deprecate tokenizer for processing_class
* Extend chage across Seq2Seq trainer and docs
* Add tests
* Update to FutureWarning and add deprecation version
* Add jamba arch
* apply "make fix-copies" changes
* fix link to model in JambaConfig docstring
* Add n_ctx in modeling file because repo-consistency wants that
* Add jamba to flash attention and sdpa documentation
* mamba dt_proj quant fix now works for LoRA as well
* override test_left_padding_compatibility and use a more permissive tolerance. left padding numerical difference are accentuated by mamba layers
* add jamba to tokenization auto
* fix comments of shape (PR #24 in the model page: https://huggingface.co/ai21labs/Jamba-v0.1/discussions/24)
* simple PR fixes
* remove unnecessary kwargs from JambaAttentionDecoderLayer and JambaMambaDecoderLayer
* remove the LoRA hack for the mamba dt_proj bias. It was solved in huggingface/peft#1530 (https://github.com/huggingface/peft/pull/1530)
* Add copied comment on JambaMLP (it's the same as MixtralMLP)
* remove padding_mask warnings. It's not supported anymore
* fix docstring. Float instead of int
* A few more minor PR fixes
* (1) lowercase names for mamba layernorms (2) remove _apply_inner_layernorms and do it directly in the forward pass
* Return None attention weights from mamba layers. Append to all attentions only if not None.
* remove some leftover jamba archive lists
* Better separation between expert vs non-expert layers. non-expert layers return None as router_logits, and it is not concatenated to all_router_logits returned from JambaModel
* no need to take router_logits at config.expert_layer_offset anymore. result.router_logits now holds results only for expert layers
* Add Jamba paper on READMEs
* (1) rename n_ctx -> max_position_embeddings (2) don't use it in the modeling file since it's not needed (set it as an exception to check_config_attributes)
* Add copied from comment
* remove the code path for apply_inner_layernorms=False. Jamba always has the inner mamba layernorms
* clearer docstring for _convert_to_standard_cache
* style fixes
* Change calc_logits_for_entire_prompt (bool) to num_logits_to_keep (int). Adapt assisted decoding code tp use it. Also small change in low memory beam search decoding path to support this new int value in model_inputs
* rename test so it still overrides what its meant to override
* draft
* oups
* nit
* remove more complexe logic
* fix names used in config
* fix fix fix
* style
* fix some more failing tests
* generate did not init the cache 🙃
* more small nits
* typo
* config.mamba_expand * config.hidden_size for the intermediate size of the mamba shapes
* fix init of pkv with torch.tensor()
* empty tensor
* fix some init issues
* stupid changes required by generate because it does not even support it's own DynamicCache class
* more fixes
* fix general assisted gen cache_position bug
* tests passing
* Add offsets and periods as SPECIAL_CASES_TO_ALLOW in check_config_attributes.py
* fix reorder_cache to reorder mamba states and override some more functions in HybridMambaAttentionDynamicCache
* no need to override test_past_key_values_format() and _check_past_key_values_for_generate() in tests anymore
* fix docstrings and typehints for past_key_values
* style fixes
* fix docs
* change typehint due to copy from Mixtral
* forgot import
* import order
* Add configuration_jamba and modeling_jamba to not_doctested because the model is too big to download (in docstring of JambaForCausalLM.forward)
* Add integration test with tiny tandom Jamba model on hub
* fix flash attention cache shapes
* bring back forgotten hidden states
* rename HybridMambaAttentionDynamicCache.seqlen_offset to has_previous_state (and make bool) and bugfix - it should be set to True after a finished forward pass of the entire model
* align integration test after modeling fixes
* bugfix - mamba can use precomputed states only of forward pass is on a single token
* bugfix - mamba can use precomputed states only if they match the batch size
* typo
* remove making _prepare_4d_causal_attention_mask a leaf function
* stop using past_seq_len.get_seq_length(). Use cache positions instead. Adjust test (test_decoder_model_past_with_large_inputs) accordingly
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
* add support for qwen2 MoE models
* update docs
* add support for qwen2 MoE models
* update docs
* update model name & test
* update readme
* update class names & readme & model_doc of Qwen2MoE.
* update architecture name
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* update modeling_qwen2_moe.py
* fix model architecture
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* update modeling_qwen2_moe.py
* fix model architecture
* fix style
* fix test when there are sparse and non sparse layers
* fixup
* Update README.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixup
* fixup
* add archive back
* add support for qwen2 MoE models
* update docs
* update model name & test
* update readme
* update class names & readme & model_doc of Qwen2MoE.
* update architecture name
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* update modeling_qwen2_moe.py
* fix model architecture
* fixup
* fix qwen2_moe tests
* use Qwen2Tokenizer instead of Qwen2MoeTokenizer
* fix style
* fix test when there are sparse and non sparse layers
* fixup
* add archive back
* fix integration test
* fixup
---------
Co-authored-by: bozheng-hit <dsoul0621@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* only dir not even init
* init
* tokenizer removed and reference of codegen added
* modeling file updated a lot remaining app_rotary_emb
* conversion script done
* conversion script fixed, a lot of factoring done and most tests pass
* added token_clf and extractive_QA_head
* integration tests pass
* flash attn tests pass!
* config done
* more docs in modeling file
* some style fix
* style and others
* doc test error fix
* more doc fix
* some attention fixes
* most fixes
* style and other fixes
* docs fix and config
* doc fix
* some comments
* conversion script updated
* conversion script updated
* Revert "conversion script updated"
This reverts commit e92378c54084ec0747041b113083d1746ecb6c7f.
* final comments
* add Phi to language_modeling.md
* edit phi.md file
* rebase and fix
* removed phi-1.5 example
* changed model_type from 'phi'->'mixformer-sequential'
* small change
* small change
* revert \small change
* changed mixformer-sequential->phi
* small change
* added phi-1.5 example instead of phi-1
* doc test might pass now
* rebase and small change
* added the dropout layer
* more fixes
* modified .md file
* very very small doc change
I'm adding accelerate as one of the libraries to install because otherwise when running the Trainer, the model errorr out with the error.
ImportError: Using the `Trainer` with `PyTorch` requires `accelerate>=0.20.1`: Please run `pip install transformers[torch]` or `pip install accelerate -U`
Further context:
1. I've tried this across different environments so I believe that the environment is not the issue.
2. I had the latest transformers library version running.
3. Typically even after install accelerate and import it, it wouldn't resolve the issue until I restart the notebook and try again.
* intiial commit
* updates
* nits
* update conversion script
* update conversion script
* use path to load
* add tips etc
* some modeling logic
* modeling update
* more nits
* nits
* normal layer norm
* update config and doc
* nits
* update doc remove unused
* update
* fix inits and stuff
* fixup
* revert wrong changes
* updates
* more nits
* add default config values to the configuration file
* fixup happy
* update
* 2 tests left
* update readmes
* more nits
* slow test and more documentation
* update readme
* fix licences
* styling
* use fast if possible when saving tokenizer
* remove todo
* remove tokenization tests
* small last nits
* Apply suggestions from code review
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* nits to skip the timout doctest
* fix integration test
* fix test
* update eos token
* update to allow fast tokenization
* styling
* fix codeLlama as well for the update post processor
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add more copied from statements
* update
* doc passes doctest
* remove `# final layer norm?`
* change docstring prompot
* update
* Update README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* don't doctest the conversion script as it requires more packages
* don't init a model in the config
* oups
* fix doctest
---------
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add all
* Revert "Delete .github directory"
This reverts commit 9b0ff7b052e2b20b629a26fb13606b78a42944d1.
* make conversion script backward compatible
* fixup
* more styling
* copy to llama changes
* fix repo consistency
* nits
* document correct classes
* updates
* more fixes
* nits
* update auto mappings
* add readmes
* smallupdates
* llama-code replace with llama_code
* make fixup
* updates to the testsing suite
* fix fast nits
* more small fixes
* fix decode
* fix template processing
* properly reset the normalizer
* nits processor
* tokenization tests pass
* styling
* last tests
* additional nits
* one test is left
* nits
Co-authored-by faabian <faabian@users.noreply.github.com>
* update failing test
* fixup
* remove decode infilling users should handle it on their onw after generation, padding can be a problem
* update
* make test slow and more meaningfull
* fixup
* doc update
* fixup
* Apply suggestions from code review
* add kwargs doc
* tokenizer requires `requires_backend`
* type requires_backends
* CodeLlama instead of LlamaCode
* more name cahnges
* nits
* make doctests happy
* small pipeline nits
* last nit
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* update
* add codellama to toctree
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Initial addition of t5forsequenceclassification
* Adding imports and adding tests
* Formatting
* Running make fix-copies
* Adding mt5forseq
* Formatting
* run make fix-copies
* Adding to docs
* Add model_parallel
* Fix bug
* Fix
* Remove TODO
* Fixing tests for T5ForSequenceClassification
* Undo changes to dependency_versions_table.py
* Change classification head to work with T5Config directly
* Change seq length to let tests pass
* PR comments for formatting
* Formatting
* Initial addition of UMT5ForSequenceClassification
* Adding to inits and formatting
* run make fix-copies
* Add doc for UMT5ForSeqClass
* Update UMT5 config
* Fix docs
* Skip torch fx test for SequenceClassification
* Formatting
* Add skip to UMT5 tests as well
* Fix umt5 tests
* Running make fix-copies
* PR comments
* Fix for change to sentence_representation
* Rename seq_len to hidden_size since that's what it is
* Use base_model to follow format of the rest of the library
* Update docs
* Extract the decoder_input_ids changes and make one liner
* Make one-liner
* Initial commit
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Cleanup config docstring
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Convert to relative imports
* Remove torch < 1.8 warning
* Restructure cos_sin header
* qkv -> query, key, value
* Refactor attention calculation
* Add a couple of config variables to account for the different checkpoints
* Successful merging of the code paths!
* Fix misplaced line in the non-parallel attention path
* Update config and tests
* Add a pad_token_id when testing
* Support output_attentions when alibi is None
* make fixup
* Skip KV cache shape test
* No more _keys_to_ignore_on_load_missing
* Simplify self attention a bit
* Simplify self attention a bit
* make fixup
* stash commit
* Some more attention mask updates
* Should pass all tests except assisted generation!
* Add big model generation test
* make fixup
* Add temporary workaround for test
* Test overrides for assisted generation
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/models/falcon/test_modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Test overrides for assisted generation
* Add generation demo
* Update copyright
* Make the docstring model actually small
* Add module-level docstring
* Remove all assertions
* Add copied from bloom
* Reformat the QKV layer
* Add copied from bloom
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Remove unused line and reformat
* No single letter variables
* Cleanup return names
* Add copied from line
* Remove the deprecated arguments blocks
* Change the embeddings test to an alibi on/off test
* Remove position_ids from FalconForQA
* Remove old check for token type IDs
* Fix the alibi path when multi_query is False
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/falcon/test_modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update config naming
* Fix typo for new_decoder_architecture
* Add some comments
* Fix docstring
* Fix docstring
* Create range in the right dtype from the start
* Review comment cleanup
* n_head_kv -> num_kv_heads
* self.alibi -> self.use_alibi
* self.num_kv -> self.num_kv_heads
* Reorder config args
* Made alibi arguments Optional
* Add all model docstrings
* Add extra checkpoints
* Add author info for Falcon
* Stop removing token_type_ids because our checkpoints shouldn't return it anymore
* Add one hopeful comment for the future
* Fix typo
* Update tests, fix cache issue for generation
* Use -1e9 instead of -inf to avoid float overflow
* Recompute the rotary embeddings much less often
* Re-enable disabled tests
* One final fix to attention mask calculation, and update tests
* Cleanup targeting falcon-40b equivalency
* Post-rebase docs update
* Update docstrings, especially in the config
* More descriptive variable names, and comments where we can't rename them
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
