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# phi-2-basic-maths
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an [GSM8K dataset](https://huggingface.co/datasets/gsm8k).
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## Model
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## Training procedure
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# phi-2-basic-maths
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an [GSM8K dataset](https://huggingface.co/datasets/gsm8k).
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## Model Description
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The objective of this model is to evaluate Phi-2's ability to provide correct solutions to reasoning problems after fine-tuning. This model was trained using techniques such as TRL, LoRA quantization, and Flash Attention.
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To test it, you can use the following code:
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```python
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import torch
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from peft import AutoPeftModelForCausalLM
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from transformers import AutoTokenizer, pipeline
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# Specify the model ID
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peft_model_id = "Menouar/phi-2-basic-maths"
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# Load Model with PEFT adapter
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model = AutoPeftModelForCausalLM.from_pretrained(
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peft_model_id,
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device_map="auto",
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torch_dtype=torch.float16
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)
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tokenizer = AutoTokenizer.from_pretrained(peft_model_id)
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pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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```
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## Training procedure
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