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:
- 18a1dd85cc498fdb8574c72b7ca24a69ef6bd9a4ef57cf47b9a21fea4a887b0b
- Size of remote file:
- 39.3 MB
- SHA256:
- a9f56226025e89bf50809b9e458aec8763409aee4d372fcbcf19ff614791f79e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.