Feature Extraction
Transformers
ONNX
dinov2
image-feature-extraction
robotics
edge-deployment
anima
forge
int8
quantized
vision
self-supervised
ros2
jetson
real-time
Eval Results (legacy)
Instructions to use robotflowlabs/dinov2-large-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robotflowlabs/dinov2-large-int8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="robotflowlabs/dinov2-large-int8")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("robotflowlabs/dinov2-large-int8") model = AutoModel.from_pretrained("robotflowlabs/dinov2-large-int8") - Notebooks
- Google Colab
- Kaggle
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