Image Feature Extraction
Transformers
Safetensors
motif_vision
feature-extraction
motif
vision-transformer
self-supervised
video
custom_code
Instructions to use Motif-Technologies/Motif-Vision-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Motif-Technologies/Motif-Vision-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="Motif-Technologies/Motif-Vision-Encoder", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Motif-Technologies/Motif-Vision-Encoder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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| Model | Training<br>data | DAVIS S<br>J&F β | DAVIS M<br>J&F β | DAVIS L<br>J&F β | ImageNet-1K<br>lin. probe β | ADE20K<br>mIoU β | K400 β |
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| **Motif Vision Encoder** | 0.5B | **
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| DINOv3 | 1.7B | <u>71.1</u> | <u>79.7</u> | <u>83.3</u> | 88.4 | **55.9** | <u>87.8</u> |
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| Web-DINO | 2B | 57.2 | 65.8 | 69.5 | 85.9 | 42.7 | 86.8 |
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| PEcore | 5.4B | 48.2 | 53.1 | 49.8 | **89.3** | 38.9 | **87.9** |
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| Model | Training<br>data | DAVIS S<br>J&F β | DAVIS M<br>J&F β | DAVIS L<br>J&F β | ImageNet-1K<br>lin. probe β | ADE20K<br>mIoU β | K400 β |
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| **Motif Vision Encoder** | 0.5B | **73.8** | **80.4** | **83.4** | 87.4 | <u>52.0</u> | 87.4 |
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| DINOv3 | 1.7B | <u>71.1</u> | <u>79.7</u> | <u>83.3</u> | 88.4 | **55.9** | <u>87.8</u> |
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| Web-DINO | 2B | 57.2 | 65.8 | 69.5 | 85.9 | 42.7 | 86.8 |
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| PEcore | 5.4B | 48.2 | 53.1 | 49.8 | **89.3** | 38.9 | **87.9** |
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