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llms: add models
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.gitignore
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@ -23,6 +23,7 @@ lib/
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lib64/
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parts/
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sdist/
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models
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var/
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wheels/
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models/
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@ -20,10 +20,13 @@ DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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LLM_MODEL_CONFIG = {
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"flan-t5-base": os.path.join(MODEL_PATH, "flan-t5-base"),
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"vicuna-13b": os.path.join(MODEL_PATH, "vicuna-13b"),
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"vicuna-7b": os.path.join(MODEL_PATH, "vicuna-7b"),
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"text2vec": os.path.join(MODEL_PATH, "text2vec-large-chinese"),
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"sentence-transforms": os.path.join(MODEL_PATH, "all-MiniLM-L6-v2"),
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"codegen2-7b": os.path.join(MODEL_PATH, ""),
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"codegen2-1b": os.path.join(MODEL_PATH, "codegen2-1B"),
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"codet5p-2b": os.path.join(MODEL_PATH, "codet5p-2b"),
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"chatglm-6b-int4": os.path.join(MODEL_PATH, "chatglm-6b-int4"),
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"chatglm-6b": os.path.join(MODEL_PATH, "chatglm-6b"),
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}
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# Load model config
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13
pilot/server/chat_adapter.py
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13
pilot/server/chat_adapter.py
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@ -0,0 +1,13 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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class BaseChatAdpter:
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"""The Base class for chat with llm models. it will match the model,
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and fetch output from model"""
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def match(self, model_path: str):
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return True
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def get_generate_stream_func(self):
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pass
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@ -30,7 +30,6 @@ model_path = LLM_MODEL_CONFIG[CFG.LLM_MODEL]
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ml = ModelLoader(model_path=model_path)
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model, tokenizer = ml.loader(num_gpus=1, load_8bit=ISLOAD_8BIT, debug=ISDEBUG)
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#model, tokenizer = load_model(model_path=model_path, device=DEVICE, num_gpus=1, load_8bit=True, debug=False)
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class ModelWorker:
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def __init__(self):
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