Instructions to use abaddon182/b2aa1a11-96d3-4e22-8876-0b504590d7f8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use abaddon182/b2aa1a11-96d3-4e22-8876-0b504590d7f8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-random-GemmaForCausalLM") model = PeftModel.from_pretrained(base_model, "abaddon182/b2aa1a11-96d3-4e22-8876-0b504590d7f8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c65862deb085c3df9ddd410a689eb4fe3303d8669cdf81b71f491756c62255eb
- Size of remote file:
- 34.3 MB
- SHA256:
- a63c485bbbab0efcfc1ffe32fd177108a9f70be1875ea3aacad3c4f064a5974b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.