Instructions to use hf-internal-testing/tiny-random-DeiTForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DeiTForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-DeiTForImageClassification") 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-DeiTForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-DeiTForImageClassification") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
7f645d9 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:62a5d51f43cb59319e37f2d0c4d429e784e41b2d8b4d554c4a6d53bfcbd28739
size 176900
|