Instructions to use FatCat87/taopanda-2_1a63cef3-a8eb-43e4-9e58-ab6c9ca06368 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FatCat87/taopanda-2_1a63cef3-a8eb-43e4-9e58-ab6c9ca06368 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "FatCat87/taopanda-2_1a63cef3-a8eb-43e4-9e58-ab6c9ca06368") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 833a1ca94b6f738cefaf19fd2270bea8ea63bf53ca5bb5a76bfbe0cc65f08bcc
- Size of remote file:
- 6.07 kB
- SHA256:
- b25452f89f1bf85dbb73c17221b4a57ca07f6131e4270640c596e17470696bb1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.