59 lines
2.9 KiB
Python
59 lines
2.9 KiB
Python
model_name = "Qwen"
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cmd_to_install = "`pip install -r request_llms/requirements_qwen.txt`"
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from toolbox import ProxyNetworkActivate, get_conf
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from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
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# ------------------------------------------------------------------------------------------------------------------------
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# 🔌💻 Local Model
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# ------------------------------------------------------------------------------------------------------------------------
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class GetQwenLMHandle(LocalLLMHandle):
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def load_model_info(self):
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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self.model_name = model_name
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self.cmd_to_install = cmd_to_install
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def load_model_and_tokenizer(self):
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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# from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers.generation import GenerationConfig
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with ProxyNetworkActivate('Download_LLM'):
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model_id = get_conf('QWEN_MODEL_SELECTION') #在这里更改路径，如果你已经下载好了的话，同时，别忘记tokenizer
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self._tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, resume_download=True)
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# use fp16
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model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", trust_remote_code=True).eval()
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model.generation_config = GenerationConfig.from_pretrained(model_id, trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
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self._model = model
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return self._model, self._tokenizer
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def llm_stream_generator(self, **kwargs):
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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def adaptor(kwargs):
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query = kwargs['query']
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max_length = kwargs['max_length']
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top_p = kwargs['top_p']
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temperature = kwargs['temperature']
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history = kwargs['history']
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return query, max_length, top_p, temperature, history
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query, max_length, top_p, temperature, history = adaptor(kwargs)
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for response in self._model.chat_stream(self._tokenizer, query, history=history):
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yield response
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def try_to_import_special_deps(self, **kwargs):
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# import something that will raise error if the user does not install requirement_*.txt
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# 🏃♂️🏃♂️🏃♂️ 主进程执行
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import importlib
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importlib.import_module('modelscope')
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# ------------------------------------------------------------------------------------------------------------------------
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# 🔌💻 GPT-Academic Interface
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# ------------------------------------------------------------------------------------------------------------------------
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predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetQwenLMHandle, model_name) |