Instructions to use prithivMLmods/High_Res-vs-Low_Res with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/High_Res-vs-Low_Res with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/High_Res-vs-Low_Res") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/High_Res-vs-Low_Res") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/High_Res-vs-Low_Res", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-628/optimizer.pt from prithivMLmods/High_Res-vs-Low_Res: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/High_Res-vs-Low_Res/resolve/main/checkpoint-628/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/High_Res-vs-Low_Res/checkpoint-628/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/High_Res-vs-Low_Res/resolve/main/checkpoint-628/optimizer.pt
687 MB
- Xet hash:
- 602ab001075869f842681d69e8630349ad06faf398c47a9070bdecdae7fcf22e
- Size of remote file:
- 687 MB
- SHA256:
- 4f5afa2f1883e4fd354819f6601bbb612137384bb9cbf3c67f4a8554fedd6919
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.