Instructions to use ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/zephyr-sft") model = PeftModel.from_pretrained(base_model, "ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08/resolve/main/training_args.bin
- Command line
-
hf download hf://ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ajtaltarabukin2022/8a4bb738-86f6-4be5-ac9c-d23e9000eb08/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- e848c85c33fa167209c9fa41edd07d5d163c7a985540f36df56d654669ab1cb1
- Size of remote file:
- 6.78 kB
- SHA256:
- db20cb839256df350d4af4c0609c57ba0293c795baf9bb8fa27658a11597a91f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.