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:
- 52d66bc5738a7cda7638a50032864b417161dd16518ea0bdb8e6fcd19081a86e
- Size of remote file:
- 15 kB
- SHA256:
- 254239861923df0d7f8a0b2c4b0af95b72ea41a4cefe224f8734022aa686bbc3
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