Instructions to use dimasik2987/4bdd484a-3e63-4ba5-b86a-5dca922ef9e2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/4bdd484a-3e63-4ba5-b86a-5dca922ef9e2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "dimasik2987/4bdd484a-3e63-4ba5-b86a-5dca922ef9e2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4021150e6e7946b33a34d33608643716aa68097d1cc80789368ed9011c6005c8
- Size of remote file:
- 14.2 kB
- SHA256:
- d1aefd6b5cb7ab5293be3b57c5a81d7e2a62b44d9e7b6cc213897ed1dd28dec5
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