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| model_name = "Qwen" | |
| cmd_to_install = "`pip install -r request_llm/requirements_qwen.txt`" | |
| from transformers import AutoModel, AutoTokenizer | |
| import time | |
| import threading | |
| import importlib | |
| from toolbox import update_ui, get_conf | |
| from multiprocessing import Process, Pipe | |
| from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns, SingletonLocalLLM | |
| # ------------------------------------------------------------------------------------------------------------------------ | |
| # 🔌💻 Local Model | |
| # ------------------------------------------------------------------------------------------------------------------------ | |
| class GetONNXGLMHandle(LocalLLMHandle): | |
| def load_model_info(self): | |
| # 🏃♂️🏃♂️🏃♂️ 子进程执行 | |
| self.model_name = model_name | |
| self.cmd_to_install = cmd_to_install | |
| def load_model_and_tokenizer(self): | |
| # 🏃♂️🏃♂️🏃♂️ 子进程执行 | |
| import os, glob | |
| import os | |
| import platform | |
| from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig | |
| model_id = 'qwen/Qwen-7B-Chat' | |
| revision = 'v1.0.1' | |
| self._tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision, trust_remote_code=True) | |
| # use fp16 | |
| model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", revision=revision, trust_remote_code=True, fp16=True).eval() | |
| 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 | |
| self._model = model | |
| return self._model, self._tokenizer | |
| def llm_stream_generator(self, **kwargs): | |
| # 🏃♂️🏃♂️🏃♂️ 子进程执行 | |
| def adaptor(kwargs): | |
| query = kwargs['query'] | |
| max_length = kwargs['max_length'] | |
| top_p = kwargs['top_p'] | |
| temperature = kwargs['temperature'] | |
| history = kwargs['history'] | |
| return query, max_length, top_p, temperature, history | |
| query, max_length, top_p, temperature, history = adaptor(kwargs) | |
| for response in self._model.chat(self._tokenizer, query, history=history, stream=True): | |
| yield response | |
| def try_to_import_special_deps(self, **kwargs): | |
| # import something that will raise error if the user does not install requirement_*.txt | |
| # 🏃♂️🏃♂️🏃♂️ 主进程执行 | |
| import importlib | |
| importlib.import_module('modelscope') | |
| # ------------------------------------------------------------------------------------------------------------------------ | |
| # 🔌💻 GPT-Academic Interface | |
| # ------------------------------------------------------------------------------------------------------------------------ | |
| predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetONNXGLMHandle, model_name) |