Instructions to use hf-internal-testing/tiny-random-GroupViTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GroupViTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-GroupViTModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-GroupViTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-GroupViTModel") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights
Browse files- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:ea0613568123db0f357673a23c1b3aa037a784fabd85f84b7f1e459a09837433
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size 4701353
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