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:
- c87f1a05256a9d542c8d8291cd35b10bd8a01e219c8aa14731f8bb588e356a3d
- Size of remote file:
- 844 MB
- SHA256:
- 243a3d33e49c94901a70985209995da93dd3e6077d3bbf560da6acd43ffc6aba
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