PEFT
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  ---
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  license: bigcode-openrail-m
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  datasets:
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  ## Intended use
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- The model follows instructions provided in the input. You should always preface your input with "Question: " and finish it with "Answer:", for example: "Question: Please write a function in Python that performs bubble sort.\n\nAnswer:"
 
 
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  **Feel free to share your generations in the Community tab!**
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  from peft import PeftModel
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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- peft_checkpoint = "bigcode/astraios-1b-lora"
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  checkpoint = "bigcode/starcoderbase-1b"
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  model = AutoModelForCausalLM.from_pretrained(checkpoint)
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  model = PeftModel.from_pretrained(model, peft_checkpoint)
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  tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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  model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
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- inputs = tokenizer.encode("Question: Please write a function in Python that performs bubble sort.\n\nAnswer:", return_tensors="pt").to(device)
 
 
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  outputs = model.generate(inputs)
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  print(tokenizer.decode(outputs[0]))
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  ```
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  # Citation
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  ```bibtex
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- ```
 
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+
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  ---
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  license: bigcode-openrail-m
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  datasets:
 
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  ## Intended use
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+ The model follows instructions provided in the input. You should always preface your input with "Question: " and finish it with "Answer:", for example: "Question: Please write a function in Python that performs bubble sort.
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+
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+ Answer:"
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  **Feel free to share your generations in the Community tab!**
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  from peft import PeftModel
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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+ peft_checkpoint = bigcode/astraios-1b-lora
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  checkpoint = "bigcode/starcoderbase-1b"
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  model = AutoModelForCausalLM.from_pretrained(checkpoint)
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  model = PeftModel.from_pretrained(model, peft_checkpoint)
 
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  tokenizer = AutoTokenizer.from_pretrained(checkpoint)
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  model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
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+ inputs = tokenizer.encode("Question: Please write a function in Python that performs bubble sort.
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+
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+ Answer:", return_tensors="pt").to(device)
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  outputs = model.generate(inputs)
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  print(tokenizer.decode(outputs[0]))
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  ```
 
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  # Citation
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  ```bibtex
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+ ```