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--- |
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language: |
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- en |
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--- |
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## Ars model |
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This model was trained on stanford alpaca dataset |
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## To Run: |
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from peft import PeftModel |
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from transformers import LLaMATokenizer, LLaMAForCausalLM, GenerationConfig |
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tokenizer = LLaMATokenizer.from_pretrained("decapoda-research/llama-7b-hf") |
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model = LLaMAForCausalLM.from_pretrained( |
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"decapoda-research/llama-7b-hf", |
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load_in_8bit=True, |
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device_map="auto", |
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)\ |
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model = PeftModel.from_pretrained(model, "patulya/ars") |
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PROMPT = """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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{your_instruction} |
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\### Response:""" |
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inputs = tokenizer( |
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PROMPT, |
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return_tensors="pt", |
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) |
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input_ids = inputs["input_ids"].cuda() |
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generation_config = GenerationConfig(\ |
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temperature=0.6,\ |
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top_p=0.95,\ |
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repetition_penalty=1.15,\ |
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) |
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print("Generating...") |
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generation_output = model.generate(\ |
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input_ids=input_ids,\ |
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generation_config=generation_config,\ |
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return_dict_in_generate=True,\ |
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output_scores=True,\ |
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max_new_tokens=128,\ |
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) |
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for s in generation_output.sequences: print(tokenizer.decode(s)) |
