Instructions to use shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Mistral-7b-128k") model = PeftModel.from_pretrained(base_model, "shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5/resolve/main/adapter_model.bin
- Command line
-
hf download hf://shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- ce22ceaa1ba284efe38c616077e2335501f1c86a95640079789bccdfcad003a6
- Size of remote file:
- 84 MB
- SHA256:
- 639b3c7e249d59b81892b66d87b25fc5e7509ec072c79733f0cc2a24341df2f3
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