Instructions to use nateraw/rare-puppers-123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/rare-puppers-123 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nateraw/rare-puppers-123") 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("nateraw/rare-puppers-123") model = AutoModelForImageClassification.from_pretrained("nateraw/rare-puppers-123", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba0856fdb2580f200b7e0e62ee1f1a912da7e834c4ba4ee73461c6f318f77d47
- Size of remote file:
- 343 MB
- SHA256:
- 8f17a6d63eeccdd44a9684258fa4e0ada9c22eaee54e2968c94d5a0dd59e5521
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.