Instructions to use shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2/resolve/main/adapter_model.bin
- Command line
-
hf download hf://shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/shibajustfor/ea03cef2-5c92-4dac-aa75-f55482a8f8c2/resolve/main/adapter_model.bin
336 MB
- Xet hash:
- 3f47eadb4f3119c21fa50c3a7f28110f6b17fc926a3675a359b9ecd6251f8ffe
- Size of remote file:
- 336 MB
- SHA256:
- 0648ab80710ca7da46bf1399fbc0688fa9c634924c89bd93d1128a4835265548
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