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)# pip install -U transformers accelerate # 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
docs(README): remove Citation section
Browse filesDrop the ## Citation heading and its bibtex block; License is now the final section.
README.md
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Released under the **MIT License** (see `LICENSE`). The model was trained on data governed by the
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respective dataset licenses; downstream users are responsible for compliance with those terms.
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## Citation
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```bibtex
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@misc{motif_vision_encoder,
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title = {Motif Vision Encoder: a unified image/video self-supervised vision encoder},
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author = {Motif Technologies},
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year = {2026},
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howpublished = {\url{https://huggingface.co/Motif-Technologies/Motif-Vision-Encoder-7B}}
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}
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```
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Released under the **MIT License** (see `LICENSE`). The model was trained on data governed by the
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respective dataset licenses; downstream users are responsible for compliance with those terms.
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