Instructions to use dada22231/6c53732c-b110-4205-80dc-07c31fcc0444 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6c53732c-b110-4205-80dc-07c31fcc0444 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-llama-2-7b") model = PeftModel.from_pretrained(base_model, "dada22231/6c53732c-b110-4205-80dc-07c31fcc0444") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cd1d55295b6565de49d811afd462908afa2e21b3f9e038c629568c1ab04d6a6
- Size of remote file:
- 15 kB
- SHA256:
- 10a74d864a26b32c75d69c44345c9b7a8f1f321205137928fe83ad7becf322e5
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