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:
- 69adeec4deb985307db95ec5dfb8afeeeb2ba8d4f9af55c45e019d8ce6c49e3e
- Size of remote file:
- 15 kB
- SHA256:
- 2b93ab6fe4052eb51329dfb5a38cbcab1d7048f58f9e40085c3e793b5387dd38
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