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add Glm (#33823)

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* Create modular_glm.py

* Update modular_glm.py

* Finalize architecture without all attentions

* Add all attentions modules

* Finalize modular

* Update given last version

* Last update

* Finalize model

* Finalize converter

* Update convert_glm_weights_to_hf.py

* style

* style

* Create __init__.py

* Aff all inits

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Correct the rotary embeddings

* Remove apply_residual_connection_post_layernorm (always false)

* remove use_rms_norm (always true)

* remove past_layer_norm (always true)

* Update __init__.py

* Update config and license

* start adding tests and doc

* Add doc + style

* Update test_modeling_glm.py

* Add dummies

* Apply correct modeling

* Refactor attention to follow llama

* Update __init__.py

* Update convert_glm_weights_to_hf.py

* Correct bias

* remove linear_bias and pdrop (never used)

* apply modular

* Simplify converter

* remove dummies + style

* add model_input_names

* Add pretraining_tp to config for when eager attention is used

* Update modular to remove all pretraining_tp

* Update test_modeling_glm.py

* Update the __all__

* Update __all__

* Update __init__.py

* Update test_modeling_glm.py

* add revisions

* Add the correct repos and revisions

* style

* Update __init__.py

* update exports

* remove import of modular files

* style

* Apply Llama changes + refine converter

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* Update convert_glm_weights_to_hf.py

* style

* Use new modular converter

* add pretrainedmodel to init

* style

* Update test_modeling_glm.py

* Move config outside modular to please CI about docstrings

* Add dummies to please CI

* Update glm.md

* Update glm.md
This commit is contained in:
Cyril Vallez
2024-10-18 17:41:12 +02:00
committed by GitHub
parent e95ea479ee
commit 6604764007
19 changed files with 2975 additions and 4 deletions
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docs/source/en/perf_infer_gpu_one.md
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@@ -42,6 +42,7 @@ FlashAttention-2 is currently supported for the following architectures:
* [Chameleon](https://huggingface.co/docs/transformers/model_doc/chameleon#transformers.Chameleon)
* [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPModel)
* [Cohere](https://huggingface.co/docs/transformers/model_doc/cohere#transformers.CohereModel)
* [GLM](https://huggingface.co/docs/transformers/model_doc/glm#transformers.GLMModel)
* [Dbrx](https://huggingface.co/docs/transformers/model_doc/dbrx#transformers.DbrxModel)
* [DistilBert](https://huggingface.co/docs/transformers/model_doc/distilbert#transformers.DistilBertModel)
* [Gemma](https://huggingface.co/docs/transformers/model_doc/gemma#transformers.GemmaModel)
@@ -216,6 +217,7 @@ For now, Transformers supports SDPA inference and training for the following arc
* [CamemBERT](https://huggingface.co/docs/transformers/model_doc/camembert#transformers.CamembertModel)
* [Chameleon](https://huggingface.co/docs/transformers/model_doc/chameleon#transformers.Chameleon)
* [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPModel)
* [GLM](https://huggingface.co/docs/transformers/model_doc/glm#transformers.GLMModel)
* [Cohere](https://huggingface.co/docs/transformers/model_doc/cohere#transformers.CohereModel)
* [data2vec_audio](https://huggingface.co/docs/transformers/main/en/model_doc/data2vec#transformers.Data2VecAudioModel)
* [Dbrx](https://huggingface.co/docs/transformers/model_doc/dbrx#transformers.DbrxModel)