Instructions to use CodCodingCode/llama-medical-diagnosis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CodCodingCode/llama-medical-diagnosis with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("aaditya/Llama3-OpenBioLLM-8B") model = PeftModel.from_pretrained(base_model, "CodCodingCode/llama-medical-diagnosis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f4cb52db8708ec751eb0f3586bea98cc203d85f21f704134254889a35f24674
- Size of remote file:
- 54.6 MB
- SHA256:
- 6eed7332479b1224883cd7de2af3280891c61faef9cb18107ef8fa2fd7617b36
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.