3 Commits

Author	SHA1	Message	Date
Quentin Gallouédec	de24fb63ed	Use HF papers (#38184) ... * Use hf papers * Hugging Face papers * doi to hf papers * style	2025-06-13 11:07:09 +00:00
Steven Liu	c0f8d055ce	[docs] Redesign (#31757) ... * toctree * not-doctested.txt * collapse sections * feedback * update * rewrite get started sections * fixes * fix * loading models * fix * customize models * share * fix link * contribute part 1 * contribute pt 2 * fix toctree * tokenization pt 1 * Add new model (#32615) * v1 - working version * fix * fix * fix * fix * rename to correct name * fix title * fixup * rename files * fix * add copied from on tests * rename to `FalconMamba` everywhere and fix bugs * fix quantization + accelerate * fix copies * add `torch.compile` support * fix tests * fix tests and add slow tests * copies on config * merge the latest changes * fix tests * add few lines about instruct * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * fix tests --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * "to be not" -> "not to be" (#32636) * "to be not" -> "not to be" * Update sam.md * Update trainer.py * Update modeling_utils.py * Update test_modeling_utils.py * Update test_modeling_utils.py * fix hfoption tag * tokenization pt. 2 * image processor * fix toctree * backbones * feature extractor * fix file name * processor * update not-doctested * update * make style * fix toctree * revision * make fixup * fix toctree * fix * make style * fix hfoption tag * pipeline * pipeline gradio * pipeline web server * add pipeline * fix toctree * not-doctested * prompting * llm optims * fix toctree * fixes * cache * text generation * fix * chat pipeline * chat stuff * xla * torch.compile * cpu inference * toctree * gpu inference * agents and tools * gguf/tiktoken * finetune * toctree * trainer * trainer pt 2 * optims * optimizers * accelerate * parallelism * fsdp * update * distributed cpu * hardware training * gpu training * gpu training 2 * peft * distrib debug * deepspeed 1 * deepspeed 2 * chat toctree * quant pt 1 * quant pt 2 * fix toctree * fix * fix * quant pt 3 * quant pt 4 * serialization * torchscript * scripts * tpu * review * model addition timeline * modular * more reviews * reviews * fix toctree * reviews reviews * continue reviews * more reviews * modular transformers * more review * zamba2 * fix * all frameworks * pytorch * supported model frameworks * flashattention * rm check_table * not-doctested.txt * rm check_support_list.py * feedback * updates/feedback * review * feedback * fix * update * feedback * updates * update --------- Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>	2025-03-03 10:33:46 -08:00
松本和真	96bf3d6cc5	Add diffllama (#34083) ... * first adding diffllama * add Diff Attention and other but still with errors * complate make attention Diff-Attention * fix some bugs which may be caused by transformer-cli while adding model * fix a bug caused by forgetting KV cache... * Update src/transformers/models/diffllama/modeling_diffllama.py You don't need to divide by 2 if we use same number of attention heads as llama. instead you can just split in forward. Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fit to changeing "num_heads // 2" place Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py new codes are more meaningful than before Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py new codes are more meaningful than before Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fit to changeing "num_heads // 2" place Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fix 2times divide by sqrt(self.head_dim) Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fix 2times divide by sqrt(self.head_dim) Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fit to changeing "num_heads // 2" place. and more visible Co-authored-by: Minho Ryu <ryumin93@gmail.com> * I found Attention missed implemented from paper still on e072544a3b. * re-implemented * adding groupnorm Co-authored-by: Minho Ryu <ryumin93@gmail.com> * align with transformers code style Co-authored-by: Minho Ryu <ryumin93@gmail.com> * fix typo Co-authored-by: Minho Ryu <ryumin93@gmail.com> * adding groupnorm Co-authored-by: Minho Ryu <ryumin93@gmail.com> * change SdpaAttention to DiffSdpaAttention Co-authored-by: Minho Ryu <ryumin93@gmail.com> * fix bug * Update src/transformers/models/diffllama/modeling_diffllama.py resolve "not same outputs" problem Co-authored-by: Minho Ryu <ryumin93@gmail.com> * fix bugs of places of "GroupNorm with scale" and etc * Revert "fix bugs of places of "GroupNorm with scale" and etc" This reverts commit 26307d92f6. * simplify multiple of attention (matmul) operations into one by repeating value_states Co-authored-by: Minho Ryu <ryumin93@gmail.com> * simplify multiple of attention (matmul) operations into one by repeating value_states Co-authored-by: Minho Ryu <ryumin93@gmail.com> * simplify multiple of attention (matmul) operations into one by repeating value_states Co-authored-by: Minho Ryu <ryumin93@gmail.com> * remove missed type * add diffllama model_doc * apply make style/quality * apply review comment about model * apply review comment about test * place diffllama alphabetically on the src/transformers/__init__.py * fix forgot code * Supports parameters that are not initialized with standard deviation 0 in the conventional method * add DiffLlamaConfig to CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK on utils/check_config_docstrings.py * remove unused property of config * add to supported model list * add to spda supported model list * fix copyright, remove pretraining_tensor_parallel, and modify for initialization test * remove unused import and etc. * empty commit * empty commit * empty commit * apply modular transformers but with bugs * revert prev commit * create src/transformers/model/diffllama/modular_diffllama.py * run utils/modular_model_converter.py * empty commit * leaner modular diffllama * remove more and more in modular_diffllama.pt * remove more and more in modular_diffllama.pt * resolve missing docstring entries * force reset * convert modular --------- Co-authored-by: Minho Ryu <ryumin93@gmail.com>	2025-01-07 11:34:56 +01:00