Instructions to use GoYM/gemma-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use GoYM/gemma-ft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-4b-pt") model = PeftModel.from_pretrained(base_model, "GoYM/gemma-ft") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ccd31462a1799d2693fc389acc661b198d3b90aa19da2dab535078ad7cee964
- Size of remote file:
- 2.84 GB
- SHA256:
- c7876fa1ef86fd5242ac486df4dd0eab8955cd4f4c697469023236e531fec53b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.