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:
- 13a126cde77dd25bc0fd869aea1d8fbe9d03cd090cdaa8b25f34e1e2b516265c
- Size of remote file:
- 15 kB
- SHA256:
- 573e6fcf7b7cf83fdd9ada858d3852156f62fcf32aa7eac75f225c9288908f7f
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