Instructions to use eeeebbb2/d71138ac-096d-47bd-b575-b4e14a1f8fc9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use eeeebbb2/d71138ac-096d-47bd-b575-b4e14a1f8fc9 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "eeeebbb2/d71138ac-096d-47bd-b575-b4e14a1f8fc9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc229b0d76f4badf8be1ab0f08dffe66c78e30f6aae6286c580562c570df353e
- Size of remote file:
- 336 MB
- SHA256:
- 57bf5920d7a060f1eff0c86967094f605cd0dfa74c6bbc3c8c973f296719ad99
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