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--- |
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library_name: peft |
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--- |
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## Inference |
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``` python |
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from datasets import load_dataset |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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from peft import PeftModel |
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base_model = AutoModelForCausalLM.from_pretrained( |
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'meta-llama/Llama-2-7b-chat-hf', |
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trust_remote_code=True, |
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device_map="auto", |
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torch_dtype=torch.float16, # optional if you have enough VRAM |
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) |
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tokenizer = AutoTokenizer.from_pretrained('FinGPT/fingpt-forecaster_dow30_llama2-7b_lora') |
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model = PeftModel.from_pretrained('FinGPT/fingpt-forecaster_dow30_llama2-7b_lora') |
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model = model.eval() |
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``` |
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- PEFT 0.5.0 |
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