Instructions to use eeeebbb2/fd0ee068-8a66-4aa1-9803-9b270d06e76a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/fd0ee068-8a66-4aa1-9803-9b270d06e76a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "eeeebbb2/fd0ee068-8a66-4aa1-9803-9b270d06e76a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d921b3d4bde1a4593a6ea8f866bcaa4abead42ac30e1f5154fc09aa27bfe745e
- Size of remote file:
- 671 MB
- SHA256:
- 42809171e47b1d969ffcaa2daf05b4c9d31e29b05b6177b8a10327ddb2d2a4ca
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