Instructions to use PranomVignesh/Dogs-vs-Racoons with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PranomVignesh/Dogs-vs-Racoons with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="PranomVignesh/Dogs-vs-Racoons") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("PranomVignesh/Dogs-vs-Racoons") model = AutoModelForImageClassification.from_pretrained("PranomVignesh/Dogs-vs-Racoons", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from PranomVignesh/Dogs-vs-Racoons: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/PranomVignesh/Dogs-vs-Racoons/resolve/main/training_args.bin
- Command line
-
hf download hf://PranomVignesh/Dogs-vs-Racoons/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/PranomVignesh/Dogs-vs-Racoons/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 107eb953aed319c7b957175be0d008d5688552b0216a2f0e6a11273fe73c246f
- Size of remote file:
- 3.58 kB
- SHA256:
- dff7711a0a72c60375647b0eeda650a74c693d875927455027df8b0baf112bb9
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