Instructions to use hf-internal-testing/tiny-random-ViTMAEModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTMAEModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-ViTMAEModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ViTMAEModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ViTMAEModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
c7c2f12 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:d1f20d03c9e6c8dc61a2304b60e4bb5a08989a81bbebfb49bfec27a987873e6c
size 193843
|