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device_map

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  1. README.md +3 -0
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@@ -119,6 +119,9 @@ m.save_pretrained("nyc-savvy")
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  You might wonder if the model successfully learned anything about NYC or is the same old LLaMa2. With your prompt not adding clues, try this from the `pefttester.py` script in this repo:
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  ```python
 
 
 
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  messages = "A chat between a curious human and an assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n"
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  messages += "### Human: What museums should I visit? - My kids are aged 12 and 5"
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  messages += "### Assistant: "
 
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  You might wonder if the model successfully learned anything about NYC or is the same old LLaMa2. With your prompt not adding clues, try this from the `pefttester.py` script in this repo:
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  ```python
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+ m = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
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+ tok = LlamaTokenizer.from_pretrained(model_name)
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+
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  messages = "A chat between a curious human and an assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n"
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  messages += "### Human: What museums should I visit? - My kids are aged 12 and 5"
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  messages += "### Assistant: "