Instructions to use lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c 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, "lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c/resolve/main/adapter_model.bin
- Command line
-
hf download hf://lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/lhong4759/f632bc40-5767-4575-97e3-5c9ba00b257c/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- f337545a72dafb502a01efde48ca01b7866bb69906d10b4f29b79a4534f98824
- Size of remote file:
- 84 MB
- SHA256:
- 364cbac984768ea5d26b618328e52b1c148ae0eb6e5ed8aed91fcc9aff2c1397
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