bcc78d8fa3
* bump transformers and update attention class map name * also run the tests in docker * add mixtral e2e smoke test * fix base name for docker image in test * mixtral lora doesn't seem to work, at least check qlora * add testcase for mixtral w sample packing * check monkeypatch for flash attn multipack * also run the e2e tests in docker * use all gpus to run tests in docker ci * use privileged mode too for docker w gpus * rename the docker e2e actions for gh ci * set privileged mode for docker and update mixtral model self attn check * use fp16/bf16 for mixtral w fa2 * skip e2e tests on docker w gpus for now * tests to validate mistral and mixtral patches * fix rel import
40 lines
639 B
Plaintext
40 lines
639 B
Plaintext
--extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
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auto-gptq==0.5.1
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packaging
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peft==0.6.0
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transformers @ git+https://github.com/huggingface/transformers.git@3cefac1d974db5e2825a0cb2b842883a628be7a0
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tokenizers==0.15.0
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bitsandbytes>=0.41.1
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accelerate==0.24.1
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deepspeed
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addict
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fire
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PyYAML>=6.0
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datasets>=2.15.0
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flash-attn==2.3.3
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sentencepiece
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wandb
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einops
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xformers==0.0.22
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optimum==1.13.2
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hf_transfer
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colorama
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numba
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numpy>=1.24.4
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# qlora things
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bert-score==0.3.13
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evaluate==0.4.0
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rouge-score==0.1.2
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scipy
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scikit-learn==1.2.2
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pynvml
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art
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fschat==0.2.34
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gradio==3.50.2
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tensorboard
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# remote filesystems
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s3fs
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gcsfs
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# adlfs
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