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:
- 4250949e2b0dea0b15ccd137bd42e3073fcf28197950513e3ed08bdc44233c6f
- Size of remote file:
- 6.84 kB
- SHA256:
- ce0736df1525f4b0e1b05a18aa25bcb86979477d8ad8ca1d8cd48dd3108aa7e2
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