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:
- 1d907102dc4f11546855eed1440aae88a2dae781591bddf760ab28eb02b99b3f
- Size of remote file:
- 6.84 kB
- SHA256:
- 5b846109d958d5b4ec3fb91dd1193c4954004d27f5798b2d1998899c93e711ae
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