Instructions to use nhung03/2af7d88b-d644-4661-b17e-473663e2a8d5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/2af7d88b-d644-4661-b17e-473663e2a8d5 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, "nhung03/2af7d88b-d644-4661-b17e-473663e2a8d5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c82d9e1c219ad5f03222141d2f438d7b6a8aaf0ca0bddcef8680ede7e222874a
- Size of remote file:
- 6.78 kB
- SHA256:
- a10bf2640e091a0eb37d70f564d506388398ca85c0e3e31251b22ac8c2e35a66
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