Instructions to use beast33/76f106c0-b863-4e5f-b0bb-191144b758dc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/76f106c0-b863-4e5f-b0bb-191144b758dc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-1.1-2b-it") model = PeftModel.from_pretrained(base_model, "beast33/76f106c0-b863-4e5f-b0bb-191144b758dc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 180dccae6ffee81e151314367eb4d32ba7fd202034c9ece6410da53202cad64d
- Size of remote file:
- 6.78 kB
- SHA256:
- 651c123f84879ee8fe16a66f46cddacfb37223a1f26bc3751316ad6800e13b7c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.