Instructions to use jgayed/gemmalora120 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jgayed/gemmalora120 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-27b-it") model = PeftModel.from_pretrained(base_model, "jgayed/gemmalora120") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f91ca11676182edb4f965525d79956f7da6fe2fc1dd95633a15931d6bba981da
- Size of remote file:
- 5.69 kB
- SHA256:
- 3ef6c21cfca5f2537c2c77045da591ab94a70a2c3c6f8193b51ea235f03d35bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.