Instructions to use therealcyberlord/llama2-qlora-finetuned-medical with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use therealcyberlord/llama2-qlora-finetuned-medical with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "therealcyberlord/llama2-qlora-finetuned-medical") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -20,6 +20,12 @@ The primary objective of this fine-tuning process is to equip Llama2 with the ab
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However, it is essential to clarify that it is not designed to replace real medical professionals. Instead, its purpose is to provide helpful information to users,
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suggesting potential next steps based on the input data and the patterns it has learned from the MedText dataset.
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## Training procedure
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However, it is essential to clarify that it is not designed to replace real medical professionals. Instead, its purpose is to provide helpful information to users,
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suggesting potential next steps based on the input data and the patterns it has learned from the MedText dataset.
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Finetuned on guanaco styled instructions
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```
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###Human
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###Assistant
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```
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## Training procedure
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