Instructions to use Filimize/Dog_Breed_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Filimize/Dog_Breed_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Filimize/Dog_Breed_Classification") 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("Filimize/Dog_Breed_Classification") model = AutoModelForImageClassification.from_pretrained("Filimize/Dog_Breed_Classification") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - image-classification | |
| - pytorch | |
| - huggingpics | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: Dog_Breed_Classification | |
| results: | |
| - task: | |
| name: Image Classification | |
| type: image-classification | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9552238583564758 | |
| # Dog_Breed_Classification | |
| ## Example Images | |
| #### english bulldog | |
|  | |
| #### saint bernard | |
|  | |
| #### siberian husky | |
|  |