Instructions to use hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher") 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("hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-LevitForImageClassificationWithTeacher", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
568cc0d | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:da19bcb6ac5cc18436f4ea0370209fc531dabff6cc5b3954a2d5a2647fbd3a4a
size 28294029
|