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[LLM] Small fix to MPT Example (#8513)

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Yuwen Hu 2023-07-13 14:33:21 +08:00 committed by GitHub
parent ba0da17b40
commit bcde8ec83e
2 changed files with 4 additions and 4 deletions
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2
python/llm/example/transformers/transformers_int4/mpt/README.md
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@ -16,7 +16,7 @@ conda create -n llm python=3.9
conda activate llm conda activate llm
pip install bigdl-llm[all] # install bigdl-llm with 'all' option pip install bigdl-llm[all] # install bigdl-llm with 'all' option
pip instll einops # additional package required for mpt-7b-chat to conduct generation pip install einops # additional package required for mpt-7b-chat to conduct generation
``` ```
### 2. Config ### 2. Config

6
python/llm/example/transformers/transformers_int4/mpt/generate.py
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@ -22,14 +22,14 @@ from bigdl.llm.transformers import AutoModelForCausalLM
from transformers import AutoTokenizer from transformers import AutoTokenizer
# you could revise it based on the MPT model you choose to use # you could revise it based on the MPT model you choose to use
MPT_PROMPT_FORMAT="<human>{prompt} <bot>" MPT_PROMPT_FORMAT = "<human>{prompt} <bot>"
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Transformer INT4 example for MPT model') parser = argparse.ArgumentParser(description='Transformer INT4 example for MPT model')
parser.add_argument('--repo-id-or-model-path', type=str, default="mosaicml/mpt-7b-chat", parser.add_argument('--repo-id-or-model-path', type=str, default="mosaicml/mpt-7b-chat",
help='The huggingface repo id for the large language model to be downloaded' help='The huggingface repo id for the MPT to be downloaded'
', or the path to the huggingface checkpoint folder') ', or the path to the huggingface checkpoint folder')
parser.add_argument('--prompt', type=str, default="<human>What is AI?<bot>", parser.add_argument('--prompt', type=str, default="What is AI?",
help='Prompt to infer') help='Prompt to infer')
parser.add_argument('--n-predict', type=int, default=32, parser.add_argument('--n-predict', type=int, default=32,
help='Max tokens to predict') help='Max tokens to predict')