Instructions to use adhisetiawan/test-vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adhisetiawan/test-vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="adhisetiawan/test-vit")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("adhisetiawan/test-vit") model = AutoModel.from_pretrained("adhisetiawan/test-vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00a0ffb687af2c6eb7d2ecea5c4cc888376bfbecfb4488af4601f64107f34f92
- Size of remote file:
- 346 MB
- SHA256:
- 259f975e67af377aea4f151ae8e36255a6b2daae0c5931287f13eaf40dcfad63
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