Instructions to use frjonah/test8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use frjonah/test8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b-it") model = PeftModel.from_pretrained(base_model, "frjonah/test8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36a2448d3d574c7d2f74dcbd5bac67cf4138d9ea3723efad15b23bb50c54c933
- Size of remote file:
- 1.76 GB
- SHA256:
- 547e293faa675dc7295c16410b1c2a5fd8b1eb7941217bb0bf266c9d49413db2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.