| 使用[Firefly](https://github.com/yangjianxin1/Firefly)项目微调baichuan-13b-base。训练数据约为一百万多轮对话数据，包括项目分享的moss数据+2万条school math数据。 | |
| 更多详情见项目：[Firefly](https://github.com/yangjianxin1/Firefly) | |
| 技术细节分享：[Firefly增强Baichuan-13B的多轮对话能力](https://mp.weixin.qq.com/s/djO8Tg3emmy6wzw_rTUlcw) | |
| 训练loss： | |
| [//]: # (<img src="https://huggingface.co/YeungNLP/firefly-baichuan-13b/resolve/main/firefly-baichuan-13b-loss.jpg" width="450">) | |
|  | |
| C-Eval榜单： | |
| | Model | C-Eval | STEM | Social Science | Humanities | Other | | |
| |----------------------------------|--------|-------|----------------|------------|-------| | |
| | Baichuan-13B-Chat(官方) | 52.05 | 42.23 | 65.27 | 58.61 | 51.32 | | |
| | **firefly-baichuan-13b** | 51.36 | 44.24 | 61.65 | 54.63 | 51.68 | | |
| | chatglm2-6b(官方) | 50.45 | 41.91 | 60.73 | 59.24 | 47.82 | | |
| | **firefly-chatglm2-6b** | 49.13 | 43.6 | 58.83 | 54.48 | 45.03 | | |
| | openbuddy-llama2-13b-v11.1-bf16 | 43.36 | 39.79 | 50.28 | 44.78 | 42.13 | | |
| | chinese-alpaca-2-13b(哈工大) | 41.86 | 36.52 | 49.7 | 47.97 | 38.33 | | |
| | openbuddy-llama2-13b-v8.1-fp16 | 41.62 | 38.82 | 44.66 | 40.28 | 45.32 | | |
| | chinese-alpaca-2-7b(哈工大) | 41.48 | 35.01 | 50.08 | 43.02 | 43.87 | | |
| | belle-llama2-13B-chat-0.4M | 41.11 | 40.04 | 44.71 | 42.09 | 38.82 | | |
| | ziya-llama-13b | 39.1 | - | - | - | - | | |
| | llama-2-13b-chat(官方) | 36.38 | 33.68 | 46.38 | 34.47 | 34.1 | | |
| | lama-2-7b-chat(官方) | 35.86 | 32.85 | 40.04 | 37.37 | 36.01 | | |
| | flagalpha/Llama2-Chinese-7b-Chat | 34.54 | 35.21 | 37.9 | 33.11 | 31.7 | | |
| | yayi-13b-llama2 | 34.15 | 36.48 | 30.64 | 32.67 | 34.6 | | |
| | yayi-7b-llama2 | 30.18 | 25.88 | 38.23 | 34.56 | 26.31 | | |
| | linly-llama2-7b | 28.35 | 26.06 | 33.47 | 29.71 | 26.53 | | |
| | linly-llama2-13b | 27.86 | 27.67 | 26.95 | 27.93 | 28.95 | | |
| 单轮对话: | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| """ | |
| 单轮对话，不具有对话历史的记忆功能 | |
| """ | |
| def main(): | |
| model_name = 'YeungNLP/firefly-baichuan-13b' | |
| max_new_tokens = 500 | |
| top_p = 0.9 | |
| temperature = 0.35 | |
| repetition_penalty = 1.0 | |
| device = 'cuda' | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_name, | |
| trust_remote_code=True, | |
| low_cpu_mem_usage=True, | |
| torch_dtype=torch.float16, | |
| device_map='auto' | |
| ).to(device).eval() | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| model_name, | |
| trust_remote_code=True, | |
| # llama不支持fast | |
| use_fast=False if model.config.model_type == 'llama' else True | |
| ) | |
| # QWenTokenizer比较特殊，pad_token_id、bos_token_id、eos_token_id均为None。eod_id对应的token为<|endoftext|> | |
| if tokenizer.__class__.__name__ == 'QWenTokenizer': | |
| tokenizer.pad_token_id = tokenizer.eod_id | |
| tokenizer.bos_token_id = tokenizer.eod_id | |
| tokenizer.eos_token_id = tokenizer.eod_id | |
| text = input('User：') | |
| while True: | |
| text = text.strip() | |
| # chatglm使用官方的数据组织格式 | |
| if model.config.model_type == 'chatglm': | |
| text = '[Round 1]\n\n问：{}\n\n答：'.format(text) | |
| input_ids = tokenizer(text, return_tensors="pt", add_special_tokens=False).input_ids.to(device) | |
| # 为了兼容qwen-7b，因为其对eos_token进行tokenize，无法得到对应的eos_token_id | |
| else: | |
| input_ids = tokenizer(text, return_tensors="pt", add_special_tokens=False).input_ids.to(device) | |
| bos_token_id = torch.tensor([[tokenizer.bos_token_id]], dtype=torch.long).to(device) | |
| eos_token_id = torch.tensor([[tokenizer.eos_token_id]], dtype=torch.long).to(device) | |
| input_ids = torch.concat([bos_token_id, input_ids, eos_token_id], dim=1) | |
| with torch.no_grad(): | |
| outputs = model.generate( | |
| input_ids=input_ids, max_new_tokens=max_new_tokens, do_sample=True, | |
| top_p=top_p, temperature=temperature, repetition_penalty=repetition_penalty, | |
| eos_token_id=tokenizer.eos_token_id | |
| ) | |
| outputs = outputs.tolist()[0][len(input_ids[0]):] | |
| response = tokenizer.decode(outputs) | |
| response = response.strip().replace(tokenizer.eos_token, "").strip() | |
| print("Firefly：{}".format(response)) | |
| text = input('User：') | |
| if __name__ == '__main__': | |
| main() | |
| ``` | |
| 多轮对话: | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| def main(): | |
| model_name = 'YeungNLP/firefly-baichuan-13b' | |
| device = 'cuda' | |
| max_new_tokens = 500 # 每轮对话最多生成多少个token | |
| history_max_len = 1000 # 模型记忆的最大token长度 | |
| top_p = 0.9 | |
| temperature = 0.35 | |
| repetition_penalty = 1.0 | |
| # 加载模型 | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_name, | |
| trust_remote_code=True, | |
| low_cpu_mem_usage=True, | |
| torch_dtype=torch.float16, | |
| device_map='auto' | |
| ).to(device).eval() | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| model_name, | |
| trust_remote_code=True, | |
| # llama不支持fast | |
| use_fast=False if model.config.model_type == 'llama' else True | |
| ) | |
| # QWenTokenizer比较特殊，pad_token_id、bos_token_id、eos_token_id均为None。eod_id对应的token为<|endoftext|> | |
| if tokenizer.__class__.__name__ == 'QWenTokenizer': | |
| tokenizer.pad_token_id = tokenizer.eod_id | |
| tokenizer.bos_token_id = tokenizer.eod_id | |
| tokenizer.eos_token_id = tokenizer.eod_id | |
| # 记录所有历史记录 | |
| if model.config.model_type != 'chatglm': | |
| history_token_ids = torch.tensor([[tokenizer.bos_token_id]], dtype=torch.long) | |
| else: | |
| history_token_ids = torch.tensor([[]], dtype=torch.long) | |
| # 开始对话 | |
| utterance_id = 0 # 记录当前是第几轮对话，为了契合chatglm的数据组织格式 | |
| user_input = input('User：') | |
| while True: | |
| utterance_id += 1 | |
| # chatglm使用官方的数据组织格式 | |
| if model.config.model_type == 'chatglm': | |
| user_input = '[Round {}]\n\n问：{}\n\n答：'.format(utterance_id, user_input) | |
| user_input_ids = tokenizer(user_input, return_tensors="pt", add_special_tokens=False).input_ids | |
| # firefly的数据组织格式 | |
| # 为了兼容qwen-7b，因为其对eos_token进行tokenize，无法得到对应的eos_token_id | |
| else: | |
| input_ids = tokenizer(user_input, return_tensors="pt", add_special_tokens=False).input_ids | |
| eos_token_id = torch.tensor([[tokenizer.eos_token_id]], dtype=torch.long) | |
| user_input_ids = torch.concat([input_ids, eos_token_id], dim=1) | |
| history_token_ids = torch.concat((history_token_ids, user_input_ids), dim=1) | |
| model_input_ids = history_token_ids[:, -history_max_len:].to(device) | |
| with torch.no_grad(): | |
| outputs = model.generate( | |
| input_ids=model_input_ids, max_new_tokens=max_new_tokens, do_sample=True, top_p=top_p, | |
| temperature=temperature, repetition_penalty=repetition_penalty, eos_token_id=tokenizer.eos_token_id | |
| ) | |
| model_input_ids_len = model_input_ids.size(1) | |
| response_ids = outputs[:, model_input_ids_len:] | |
| history_token_ids = torch.concat((history_token_ids, response_ids.cpu()), dim=1) | |
| response = tokenizer.batch_decode(response_ids) | |
| print("Firefly：" + response[0].strip().replace(tokenizer.eos_token, "")) | |
| user_input = input('User：') | |
| if __name__ == '__main__': | |
| main() | |
| ``` | |