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")# pip install -U transformers accelerate # 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 model.safetensors from PranomVignesh/Dogs-vs-Racoons: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/PranomVignesh/Dogs-vs-Racoons/resolve/refs%2Fpr%2F2/model.safetensors
- Command line
-
hf download hf://PranomVignesh/Dogs-vs-Racoons@refs/pr/2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/PranomVignesh/Dogs-vs-Racoons/resolve/refs%2Fpr%2F2/model.safetensors
343 MB
- Xet hash:
- 4c4c4acd5f1d9d25c63d269f1a0bd3a00c81c5eafca07d0f55cebedcdf2c9f61
- Size of remote file:
- 343 MB
- SHA256:
- 34c2b4b52e5a20960a8e3d25c31789303a0447197260a4763f830d8230f98283
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