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:
- 688d9fcd7bd7cda17d2e6b43dc72c06a37a8a52bed285353654ccb8a41eaa937
- Size of remote file:
- 168 MB
- SHA256:
- f94a5db7ff267a7eb3790a6306dea0ff796d5226a9c83fe5dd5f52d4c77fe35d
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