Instructions to use antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d/resolve/main/training_args.bin
- Command line
-
hf download hf://antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/antimage88/395d9bb7-52e4-475e-8a8c-5638ca879a6d/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 4277181db8e23e3c9d705cf7b2fc4ec4d59480f96eefbe2b6b58fec2feb0fc3d
- Size of remote file:
- 6.84 kB
- SHA256:
- 9380ff338000e4444c1528b3792cf47a5617ad40c4be673559e7772749617391
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.