Instructions to use fats-fme/f30c7404-09c5-48b7-8562-82f69bbb90ae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fats-fme/f30c7404-09c5-48b7-8562-82f69bbb90ae with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-SOLAR-10.7B") model = PeftModel.from_pretrained(base_model, "fats-fme/f30c7404-09c5-48b7-8562-82f69bbb90ae") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64fd27681277eeea70d5413859acf59a5a9288e69df1bff0168f8f261231ed7b
- Size of remote file:
- 6.78 kB
- SHA256:
- 8bcd46ba24db175d3c3d96465223c4d461ccb485b7564b4fe6742d364889ffc9
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