Instructions to use kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004/resolve/main/training_args.bin
- Command line
-
hf download hf://kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kk-aivio/72ade028-16dc-43b8-b88f-66b29c493004/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 3c270beebbec2b2a7f39a07b86a16aab00de3bfa0eb4a8927dbd7e634e7f32b6
- Size of remote file:
- 6.78 kB
- SHA256:
- f170e9b788c77fbff741d4d7129b8f4e6bc4b4f798798fcbf723c8cac16ac908
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.