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license: apache-2.0 |
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This checkpoint is trained with: 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 |
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from peft import PeftModel |
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tokenizer = AutoTokenizer.from_pretrained("baichuan-inc/baichuan-7B", trust_remote_code=True) |
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model = AutoModelForCausalLM.from_pretrained("baichuan-inc/baichuan-7B", device_map="auto", trust_remote_code=True) |
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model = PeftModel.from_pretrained(model, "hiyouga/baichuan-7b-sft") |
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model = model.merge_and_unload() |
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query = "晚上睡不着怎么办" |
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inputs_ids = tokenizer(["<human>:{}\n<bot>:".format(query)], return_tensors="pt")["input_ids"] |
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inputs_ids = inputs_ids.to("cuda") |
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generate_ids = model.generate(input_ids) |
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output = tokenizer.batch_decode(generate_ids)[0] |
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print(output) |
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``` |
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