Instructions to use hf-internal-testing/tiny-random-Swinv2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Swinv2Model 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-Swinv2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Swinv2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Swinv2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
70aeb72 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:2df26b40f8c00afd60b81f48988b7ae9adf81deb276ce16fe14d52ac8289b384
size 327609
|