Instructions to use yashvshetty/clarke-medgemma-27b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use yashvshetty/clarke-medgemma-27b-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/medgemma-27b-text-it") model = PeftModel.from_pretrained(base_model, "yashvshetty/clarke-medgemma-27b-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3bc5fe026bc777de9528a665efeb9d556ecfdcb26806509fc2eee7033c821f8c
- Size of remote file:
- 134 MB
- SHA256:
- d29c7be9a3558233d1779ae2cc4e9123b885e7809d4ce73c7f01335993a3c128
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.