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:
- fd5d830ccc1098701cd21304d15e0d2b1dee9f0a3483085b1998506c814be149
- Size of remote file:
- 671 MB
- SHA256:
- 5cf92819c598c0f176d87f4df9c4e0c28e10ceafdf2b928e48456d66e8c369ee
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