Instructions to use qanastek/MedAlpaca-LLaMa2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use qanastek/MedAlpaca-LLaMa2-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "qanastek/MedAlpaca-LLaMa2-7B") - Notebooks
- Google Colab
- Kaggle
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: False
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- load_in_4bit: True
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## Training procedure
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Model: [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf)
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: False
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- load_in_4bit: True
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