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 training_args.bin from shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5/resolve/61fe217ee7dea3b72f84b72ebe32cddb7bcacb67/training_args.bin
- Command line
-
hf download hf://shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5@61fe217ee7dea3b72f84b72ebe32cddb7bcacb67/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/shibajustfor/a690348b-9d15-46c5-92f0-37a6633c8cd5/resolve/61fe217ee7dea3b72f84b72ebe32cddb7bcacb67/training_args.bin
6.78 kB
- Xet hash:
- adf302941c59de610c0604b7922eb498083e62d213f04ee6205da0ca1ad88cbd
- Size of remote file:
- 6.78 kB
- SHA256:
- 505557b43e25be416331683ad43acb88390303540df98ce85d55febccdfa7c5e
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