Instructions to use dzanbek/19c416b4-148d-48ab-9712-2e39930df74a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/19c416b4-148d-48ab-9712-2e39930df74a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "dzanbek/19c416b4-148d-48ab-9712-2e39930df74a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b731a4af7d93ab333c38c81e00b47e41f0acbba9b6084ccf7d0dd92bcb5996b7
- Size of remote file:
- 2.27 GB
- SHA256:
- 072e641b94bc4510d00a4910d7689a9ee7062526f66f3d194da1c0ab736fbde3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.