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 scheduler.pt from PranomVignesh/Dogs-vs-Racoons: direct link, hf CLI and curl.
- Browser
- Download file 627 Bytes
-
https://huggingface.co/PranomVignesh/Dogs-vs-Racoons/resolve/main/scheduler.pt
- Command line
-
hf download hf://PranomVignesh/Dogs-vs-Racoons/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/PranomVignesh/Dogs-vs-Racoons/resolve/main/scheduler.pt
627 Bytes
- Xet hash:
- 538ed25455ae2ac8bb03680e623249b5fce27d13579fa08a1a44bf08a4a90426
- Size of remote file:
- 627 Bytes
- SHA256:
- 57c89c7765412de4a31242f8c86f155856192e5f74b2c2681532f22cca64dd77
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