77 lines
2.2 KiB
Markdown
77 lines
2.2 KiB
Markdown
---
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title: chinese-alpaca-33b-merged
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emoji: 📚
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colorFrom: gray
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colorTo: red
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sdk: gradio
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sdk_version: 3.23.0
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app_file: app.py
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pinned: false
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---
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加入中文词表并继续预训练中文Embedding，并在此基础上继续使用指令数据集finetuning，得到的中文Alpaca-33B模型。
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模型转换用到的相关base及lora模型如下：
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- base-model: elinas/llama-30b-hf-transformers-4.29
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- lora-model: ziqingyang/chinese-alpaca-lora-33b
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详情可参考：https://github.com/ymcui/Chinese-LLaMA-Alpaca/releases/tag/v4.0
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### 使用方法参考
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1. 安装模块包
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```bash
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pip install sentencepiece
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pip install transformers>=4.28.0
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```
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2. 生成文本
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```python
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import torch
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import transformers
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from transformers import LlamaTokenizer, LlamaForCausalLM
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def generate_prompt(text):
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return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction:
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{text}
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### Response:"""
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tokenizer = LlamaTokenizer.from_pretrained('minlik/chinese-alpaca-33b-merged')
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model = LlamaForCausalLM.from_pretrained('minlik/chinese-alpaca-33b-merged').half().to('cuda')
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model.eval()
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text = '第一个登上月球的人是谁？'
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prompt = generate_prompt(text)
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input_ids = tokenizer.encode(prompt, return_tensors='pt').to('cuda')
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with torch.no_grad():
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output_ids = model.generate(
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input_ids=input_ids,
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max_new_tokens=128,
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temperature=1,
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top_k=40,
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top_p=0.9,
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repetition_penalty=1.15
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).cuda()
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output = tokenizer.decode(output_ids[0], skip_special_tokens=True)
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print(output.replace(prompt, '').strip())
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_minlik__chinese-alpaca-33b-merged)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 53.09 |
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| ARC (25-shot) | 59.3 |
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| HellaSwag (10-shot) | 78.43 |
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| MMLU (5-shot) | 57.69 |
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| TruthfulQA (0-shot) | 52.45 |
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| Winogrande (5-shot) | 76.09 |
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| GSM8K (5-shot) | 8.04 |
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| DROP (3-shot) | 39.67 |
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