Instructions to use FatCat87/taopanda-3_5cbd8b3f-9553-4538-beb8-e2b7bc77d242 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FatCat87/taopanda-3_5cbd8b3f-9553-4538-beb8-e2b7bc77d242 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Mistral-7b-64k") model = PeftModel.from_pretrained(base_model, "FatCat87/taopanda-3_5cbd8b3f-9553-4538-beb8-e2b7bc77d242") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90cbc94f2faf603c8fe04cabfa7532a69af341ad77e6276b182c47a2328ea02e
- Size of remote file:
- 15 kB
- SHA256:
- c2684bc15ac0b3eadebd60c1a740cc8abb940a581e1c8c7e15b25067d802ec7e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.