Instructions to use dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 682337c3baddc03e5eab8cf961c8d74c6f1ee89fe627e5bb7d523df22da911be
- Size of remote file:
- 336 MB
- SHA256:
- 6c696cab0a3d3a6350c331a2fa51b164096d09045d83c85832605ebb6c37a08a
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