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:
- e820de8ab9be183c2d88da862d7aca6878ef5afe7f62f8409d0c4bc61fb0755f
- Size of remote file:
- 6.78 kB
- SHA256:
- 81c8e371309675ec4c6f07da0b04740c2946a6a437bbc5b22f360e412f64d03a
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