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--- |
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license: bigscience-bloom-rail-1.0 |
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language: |
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- zh |
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--- |
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# 体验 |
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🚀 点击链接，即可体验🔗 **[http://101.68.79.42:7861/](http://101.68.79.42:7861/)** |
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## 介绍 |
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1. ✅ 对`bloom-7b`模型做了sft |
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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](https://github.com/yuanzhoulvpi2017/zero_nlp/tree/main/chinese_bloom) |
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## 🚀更新 |
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| 模型链接 | 训练的数据量 | 模型版本 | 备注 | |
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| [https://huggingface.co/yuanzhoulvpi/chinese_bloom_7b_chat](https://huggingface.co/yuanzhoulvpi/chinese_bloom_7b_chat) | 15w中文指令数据 | v1 | | |
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| [https://huggingface.co/yuanzhoulvpi/chinese_bloom_7b_chat_v2](https://huggingface.co/yuanzhoulvpi/chinese_bloom_7b_chat_v2) | 150w条中文指令数据 | v2 | 目前已经测试过效果，相较于v1，效果有所提升 | |
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| [https://huggingface.co/yuanzhoulvpi/chinese_bloom_7b_chat_v3](https://huggingface.co/yuanzhoulvpi/chinese_bloom_7b_chat_v3) | 420w条中文指令数据 | v3 | 目前效果还没测试，欢迎大家测试 | |
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## 个人感受 |
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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！ |
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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） |
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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~ |
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## 如何使用 |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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checkpoint = "yuanzhoulvpi/chinese_bloom_7b_chat"#"bigscience/bloomz-3b" #"bigscience/bloom-7b1"# "output_dir/checkpoint-8260"# |
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tokenizer = AutoTokenizer.from_pretrained(checkpoint) |
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model = AutoModelForCausalLM.from_pretrained(checkpoint).half().cuda() |
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PROMPT_DICT = { |
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"prompt_input": ( |
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"Below is an instruction that describes a task, paired with an input that provides further context. " |
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"Write a response that appropriately completes the request.\n\n" |
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"### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:" |
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), |
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"prompt_no_input": ( |
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"Below is an instruction that describes a task. " |
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"Write a response that appropriately completes the request.\n\n" |
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"### Instruction:\n{instruction}\n\n### Response:" |
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), |
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} |
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from typing import Optional |
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def generate_input(instruction:Optional[str]= None, input_str:Optional[str] = None) -> str: |
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if input_str is None: |
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return PROMPT_DICT['prompt_no_input'].format_map({'instruction':instruction}) |
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else: |
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return PROMPT_DICT['prompt_input'].format_map({'instruction':instruction, 'input':input_str}) |
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for i in range(5): |
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print("*"*80) |
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inputs = tokenizer.encode(generate_input(instruction="你是谁"), return_tensors="pt") |
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outputs = model.generate(inputs,num_beams=3, |
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max_new_tokens=512, |
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do_sample=False, |
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top_k=10, |
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penalty_alpha=0.6, |
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temperature=0.8, |
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repetition_penalty=1.2) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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## 效果 |
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不管是写代码还是写文案，`bloom-7b`在中文领域有极大的潜力 |
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- example 1 |
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- example 2 |
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- example 3 |
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- example 4 |
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- example 5 |
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