Instructions to use eeeebbb2/bd2df650-ef52-4589-a762-313905b5420e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/bd2df650-ef52-4589-a762-313905b5420e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/really-tiny-falcon-testing") model = PeftModel.from_pretrained(base_model, "eeeebbb2/bd2df650-ef52-4589-a762-313905b5420e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58c06b017b019cc9671343da93fa27597e795dd0cf177d024b1e8d43cc7d94dd
- Size of remote file:
- 6.84 kB
- SHA256:
- f6420161599e0e730186d85a914476502f5bd6fcd2b15127d1fbcd8b6cd533b2
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