Instructions to use chauhoang/f4ceaa19-6420-4b44-a08d-f9e4b1bc8dc3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chauhoang/f4ceaa19-6420-4b44-a08d-f9e4b1bc8dc3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "chauhoang/f4ceaa19-6420-4b44-a08d-f9e4b1bc8dc3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52cabdd0716367f1a4547df570bb1c4d025d607037cccc1a0a13247a040021c4
- Size of remote file:
- 84 MB
- SHA256:
- 6e26d4d5e84423ea6cc40293763b164554df6e071cf2e53c7762a6bf874c3789
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