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
assets: refine architecture figure layout and caption legibility
#5
by gkalstn0 - opened
Refines the architecture figure: bold darker captions outside blocks, title and enclosure removed for a cleaner canvas, the transformer-block callout centered at 82% width and pulled 40% closer to the stack, and the magnifier wedge attached directly to the highlighted slab. Rendered deterministically at 2658x1344.
gkalstn0 changed pull request status to merged
gkalstn0 deleted the
refs/pr/5 ref