Instructions to use hf-internal-testing/tiny-random-ViTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTModel 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-ViTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ViTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ViTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44d9e3b11565caef0629f4f503dffb32264f19a7373ac652aad06afa9846a7fa
- Size of remote file:
- 199 kB
- SHA256:
- 4b2c95587187bd726c71516ceba65be4f403fb443116621b612cfca1ec359a98
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