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:
- 19b316017e4bece81d562f3f411a500753b3f25d3606c11830d3b705146dd6ba
- Size of remote file:
- 169 MB
- SHA256:
- 7c125dd1aafa5e7583d4c20081726039e1cb69f66c81bfa920f2136f15b63ff5
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