Instructions to use ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dltjdgh0928/test_instruction") model = PeftModel.from_pretrained(base_model, "ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa/resolve/main/training_args.bin
- Command line
-
hf download hf://ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 2dbfb8d6c82ef468aa8fc434313b1c4ba2163798197f282ec12615656da7dfd6
- Size of remote file:
- 6.78 kB
- SHA256:
- 3dc701a2748f89bca49c3ae32384124e1bce2803f96d14ca2e6ae1a9ef53c7eb
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