Instructions to use minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b 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, "minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b/resolve/main/adapter_model.bin
- Command line
-
hf download hf://minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/minhnguyennnnnn/5b95903b-6ab0-44c3-acf9-6de2fef25c7b/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- bfb5129b8f24956fbf99402532d409584984b1c2c8c0324f27f3d39099762382
- Size of remote file:
- 84 MB
- SHA256:
- 67629e785363bd116cec1deb3f2589ef50dd095a87f432812574a2afb6a8e7da
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