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:
- f15b7b86b64265183afa5f597d5f257841c809545cfade15d58bcf6629f2ab2c
- Size of remote file:
- 168 MB
- SHA256:
- 53b2d1a8e9ca4c511cdc1e6fee9b93ac287908b72c782ba2512d94a16d0bef87
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