Instructions to use FatCat87/taopanda-3_b49985cb-1972-4835-840c-c05792e5f494 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FatCat87/taopanda-3_b49985cb-1972-4835-840c-c05792e5f494 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0") model = PeftModel.from_pretrained(base_model, "FatCat87/taopanda-3_b49985cb-1972-4835-840c-c05792e5f494") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 360e49d192c99f45025441917920fc7d007abd4f6d66bae21702306713808564
- Size of remote file:
- 6.2 kB
- SHA256:
- 7044ab370f50e22793bf25f1ac2aa02aad032be42bd16d0ef9d82b85e1235f84
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