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--- |
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license: llama2 |
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datasets: |
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- tatsu-lab/alpaca |
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- OpenAssistant/oasst1 |
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language: |
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- zh |
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- en |
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library_name: transformers |
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tags: |
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- baichuan |
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- lora |
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pipeline_tag: text-generation |
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inference: false |
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--- |
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A bilingual instruction-tuned LoRA model of https://huggingface.co/meta-llama/Llama-2-13b-hf |
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- Instruction-following datasets used: alpaca, alpaca-zh, open assistant |
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- Training framework: https://github.com/hiyouga/LLaMA-Efficient-Tuning |
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Usage: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer |
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tokenizer = AutoTokenizer.from_pretrained("hiyouga/Llama-2-Chinese-13b-chat") |
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model = AutoModelForCausalLM.from_pretrained("hiyouga/Llama-2-Chinese-13b-chat").cuda() |
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streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) |
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query = "晚上睡不着怎么办" |
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template = ( |
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"A chat between a curious user and an artificial intelligence assistant. " |
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"The assistant gives helpful, detailed, and polite answers to the user's questions.\n" |
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"Human: {}\nAssistant: " |
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) |
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inputs = tokenizer([template.format(query)], return_tensors="pt") |
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inputs = inputs.to("cuda") |
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generate_ids = model.generate(**inputs, max_new_tokens=256, streamer=streamer) |
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``` |
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You could also alternatively launch a CLI demo by using the script in https://github.com/hiyouga/LLaMA-Efficient-Tuning |
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```bash |
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python src/cli_demo.py --model_name_or_path hiyouga/Llama-2-Chinese-13b-chat |
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``` |
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--- |
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Loss curve: |
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