Instructions to use tkcho/dino-vits16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tkcho/dino-vits16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="tkcho/dino-vits16")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("tkcho/dino-vits16") model = AutoModel.from_pretrained("tkcho/dino-vits16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:601d22a916bf0ccca66a7c95075745c5ee3b9090b896fe47397fcdc91e09d34c
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size 87276144
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