chinese_bloom_7b_chat

体验

🚀 点击链接，即可体验🔗 http://101.68.79.42:7861/

介绍

1. ✅ 对bloom-7b模型做了sft
2. 🚀 训练代码和推理代码全部分享，可以查看链接https://github.com/yuanzhoulvpi2017/zero_nlp/tree/main/chinese_bloom

🚀更新

个人感受

1. 🎯 bloom系列的模型，在中文领域，具有极大的潜力，在经过有监督微调训练之后，效果非常惊人！
2. 🔄 bloom系列的模型，覆盖中文、英文、代码、法语、西班牙语等。即使拿来做翻译、拿来做代码生成，也都没问题！（后期将会分享相关教程）
3. 😛 当前的这个bloom-7b模型，我是非常喜欢滴，特地在8xA100机器上训练了部分数据。整体效果非常不错~

如何使用

from transformers import AutoModelForCausalLM, AutoTokenizer


checkpoint = "yuanzhoulvpi/chinese_bloom_7b_chat"#"bigscience/bloomz-3b" #"bigscience/bloom-7b1"#  "output_dir/checkpoint-8260"#
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForCausalLM.from_pretrained(checkpoint).half().cuda()

PROMPT_DICT = {
    "prompt_input": (
        "Below is an instruction that describes a task, paired with an input that provides further context. "
        "Write a response that appropriately completes the request.\n\n"
        "### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:"
    ),
    "prompt_no_input": (
        "Below is an instruction that describes a task. "
        "Write a response that appropriately completes the request.\n\n"
        "### Instruction:\n{instruction}\n\n### Response:"
    ),
}

from typing import Optional
def generate_input(instruction:Optional[str]= None, input_str:Optional[str] = None) -> str:
    if input_str is None:
        return PROMPT_DICT['prompt_no_input'].format_map({'instruction':instruction})
    else:
        return PROMPT_DICT['prompt_input'].format_map({'instruction':instruction, 'input':input_str})


for i in range(5):
    print("*"*80)

    inputs = tokenizer.encode(generate_input(instruction="你是谁"), return_tensors="pt")
    outputs = model.generate(inputs,num_beams=3,
                            max_new_tokens=512,
                            do_sample=False, 
                            top_k=10,
                            penalty_alpha=0.6,
                            temperature=0.8,
                            repetition_penalty=1.2)
    print(tokenizer.decode(outputs[0]))

效果

不管是写代码还是写文案，bloom-7b在中文领域有极大的潜力

• example 1
• example 2
• example 3
• example 4
• example 5