diff --git a/.env.template b/.env.template index 234b12738..2fb5ff649 100644 --- a/.env.template +++ b/.env.template @@ -21,7 +21,7 @@ LLM_MODEL=vicuna-13b MODEL_SERVER=http://127.0.0.1:8000 LIMIT_MODEL_CONCURRENCY=5 MAX_POSITION_EMBEDDINGS=4096 - +QUANTIZE_QLORA=True ## SMART_LLM_MODEL - Smart language model (Default: vicuna-13b) ## FAST_LLM_MODEL - Fast language model (Default: chatglm-6b) # SMART_LLM_MODEL=vicuna-13b @@ -112,4 +112,4 @@ PROXY_SERVER_URL=http://127.0.0.1:3000/proxy_address #*******************************************************************# # ** SUMMARY_CONFIG #*******************************************************************# -SUMMARY_CONFIG=FAST \ No newline at end of file +SUMMARY_CONFIG=FAST diff --git a/pilot/configs/model_config.py b/pilot/configs/model_config.py index 4cef24489..1997584a7 100644 --- a/pilot/configs/model_config.py +++ b/pilot/configs/model_config.py @@ -35,6 +35,7 @@ LLM_MODEL_CONFIG = { "chatglm-6b": os.path.join(MODEL_PATH, "chatglm-6b"), "text2vec-base": os.path.join(MODEL_PATH, "text2vec-base-chinese"), "guanaco-33b-merged": os.path.join(MODEL_PATH, "guanaco-33b-merged"), + "falcon-40b": os.path.join(MODEL_PATH, "falcon-40b"), "gorilla-7b": os.path.join(MODEL_PATH, "gorilla-7b"), "proxyllm": "proxyllm", } @@ -42,7 +43,7 @@ LLM_MODEL_CONFIG = { # Load model config ISLOAD_8BIT = True ISDEBUG = False - +QLORA = os.getenv("QUANTIZE_QLORA") == "True" VECTOR_SEARCH_TOP_K = 10 VS_ROOT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "vs_store") diff --git a/pilot/model/adapter.py b/pilot/model/adapter.py index f5e5125cc..c914195d8 100644 --- a/pilot/model/adapter.py +++ b/pilot/model/adapter.py @@ -1,12 +1,13 @@ #!/usr/bin/env python3 # -*- coding: utf-8 -*- -from functools import cache + +import torch from typing import List - -from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer, LlamaTokenizer - +from functools import cache +from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer, LlamaTokenizer, BitsAndBytesConfig from pilot.configs.model_config import DEVICE +bnb_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype="bfloat16", bnb_4bit_use_double_quant=False) class BaseLLMAdaper: """The Base class for multi model, in our project. @@ -95,19 +96,32 @@ class GuanacoAdapter(BaseLLMAdaper): model_path, load_in_4bit=True, device_map={"": 0}, **from_pretrained_kwargs ) return model, tokenizer - - -class GuanacoAdapter(BaseLLMAdaper): - """TODO Support guanaco""" + + +class FalconAdapater(BaseLLMAdaper): + """falcon Adapter""" def match(self, model_path: str): - return "guanaco" in model_path + return "falcon" in model_path - def loader(self, model_path: str, from_pretrained_kwargs: dict): - tokenizer = LlamaTokenizer.from_pretrained(model_path) - model = AutoModelForCausalLM.from_pretrained( - model_path, load_in_4bit=True, device_map={"": 0}, **from_pretrained_kwargs - ) + def loader(self, model_path: str, from_pretrained_kwagrs: dict): + tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False) + if QLORA: + model = AutoModelForCausalLM.from_pretrained( + model_path, + load_in_4bit=True, #quantize + quantization_config=bnb_config, + device_map={"": 0}, + trust_remote_code=True, + **from_pretrained_kwagrs + ) + else: + model = AutoModelForCausalLM.from_pretrained( + model_path, + trust_remote_code=True, + device_map={"": 0}, + **from_pretrained_kwagrs + ) return model, tokenizer @@ -180,6 +194,7 @@ class ProxyllmAdapter(BaseLLMAdaper): register_llm_model_adapters(VicunaLLMAdapater) register_llm_model_adapters(ChatGLMAdapater) register_llm_model_adapters(GuanacoAdapter) +register_llm_model_adapters(FalconAdapater) register_llm_model_adapters(GorillaAdapter) # TODO Default support vicuna, other model need to tests and Evaluate diff --git a/pilot/model/llm_out/falcon_llm.py b/pilot/model/llm_out/falcon_llm.py new file mode 100644 index 000000000..f4cb53eff --- /dev/null +++ b/pilot/model/llm_out/falcon_llm.py @@ -0,0 +1,54 @@ +import torch +import copy +from threading import Thread +from transformers import TextIteratorStreamer, StoppingCriteriaList, StoppingCriteria + + +def falcon_generate_output(model, tokenizer, params, device, context_len=2048): + """Fork from: https://github.com/KohakuBlueleaf/guanaco-lora/blob/main/generate.py""" + tokenizer.bos_token_id = 1 + print(params) + stop = params.get("stop", "###") + prompt = params["prompt"] + query = prompt + print("Query Message: ", query) + + input_ids = tokenizer(query, return_tensors="pt").input_ids + input_ids = input_ids.to(model.device) + + streamer = TextIteratorStreamer( + tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True + ) + + tokenizer.bos_token_id = 1 + stop_token_ids = [0] + + class StopOnTokens(StoppingCriteria): + def __call__( + self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs + ) -> bool: + for stop_id in stop_token_ids: + if input_ids[0][-1] == stop_id: + return True + return False + + stop = StopOnTokens() + + generate_kwargs = dict( + input_ids=input_ids, + max_new_tokens=512, + temperature=1.0, + do_sample=True, + top_k=1, + streamer=streamer, + repetition_penalty=1.7, + stopping_criteria=StoppingCriteriaList([stop]), + ) + + t = Thread(target=model.generate, kwargs=generate_kwargs) + t.start() + + out = "" + for new_text in streamer: + out += new_text + yield out diff --git a/pilot/server/chat_adapter.py b/pilot/server/chat_adapter.py index f87f0b24c..a311312a2 100644 --- a/pilot/server/chat_adapter.py +++ b/pilot/server/chat_adapter.py @@ -3,7 +3,6 @@ from functools import cache from typing import List - from pilot.model.llm_out.vicuna_base_llm import generate_stream @@ -95,17 +94,18 @@ class GuanacoChatAdapter(BaseChatAdpter): return guanaco_generate_stream -class GorillaChatAdapter(BaseChatAdpter): + +class FalconChatAdapter(BaseChatAdpter): """Model chat adapter for Guanaco""" def match(self, model_path: str): - return "gorilla" in model_path + return "falcon" in model_path def get_generate_stream_func(self): - from pilot.model.llm_out.gorilla_llm import generate_stream - - return generate_stream + from pilot.model.llm_out.falcon_llm import falcon_generate_output + return falcon_generate_output + class ProxyllmChatAdapter(BaseChatAdpter): def match(self, model_path: str): return "proxyllm" in model_path @@ -119,6 +119,7 @@ class ProxyllmChatAdapter(BaseChatAdpter): register_llm_model_chat_adapter(VicunaChatAdapter) register_llm_model_chat_adapter(ChatGLMChatAdapter) register_llm_model_chat_adapter(GuanacoChatAdapter) +register_llm_model_adapters(FalconChatAdapter) register_llm_model_chat_adapter(GorillaChatAdapter) # Proxy model for test and develop, it's cheap for us now.