Instructions to use huji-iml-image-hackathon-2026/validate_API with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huji-iml-image-hackathon-2026/validate_API with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="huji-iml-image-hackathon-2026/validate_API") 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("huji-iml-image-hackathon-2026/validate_API") model = AutoModelForImageClassification.from_pretrained("huji-iml-image-hackathon-2026/validate_API") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| tags: | |
| - image-classification | |
| - dummy | |
| pipeline_tag: image-classification | |
| # Dummy Image Classification Submission | |
| This is a tiny random-weight dummy model for testing a Hugging Face image-classification submission workflow. | |
| It is **not trained** and should not be used for real scoring. | |
| Expected loading pattern: | |
| ```python | |
| from transformers import AutoImageProcessor, AutoModelForImageClassification | |
| repo_id = "huji-iml-hackathon-2026/test-submission" | |
| processor = AutoImageProcessor.from_pretrained(repo_id) | |
| model = AutoModelForImageClassification.from_pretrained(repo_id, trust_remote_code=False) | |
| ``` | |
| Labels: | |
| - cat | |
| - dog | |
| - bird | |