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- Images to inference with no labeling (use foundation models to train supervised models).
- Use Gemini to auto-label images for use with Autodistill.
- Use Florence 2 to auto-label data for use in training fine-tuned object detection models.
- Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.
- GPT-4V(ision) module for use with Autodistill.
- Grounding DINO module for use with Autodistill.
autodistill-target-model-template
Public templateA template for use in creating Autodistill Target Model packages.- Use PaliGemma to auto-label data for use in training fine-tuned vision models.
autodistill-setfit
PublicTrain a SetFit model for use in text classification.autodistill-gpt-text
Publicautodistill-remote-clip
Public- EdgeSAM model for use with Autodistill.
- FastViT base model for use with Autodistill.
- GPT-4o (with Vision) module for use with Autodistill.
- GroundedSAM Base Model plugin for Autodistill
autodistill-blipv2
Public- OWL-ViT module for Autodistill.
- CoDet base model for use with Autodistill.
- YOLOv5 module for use with Autodistill.
- EfficientSAM + YOLO World base model for use with Autodistill.
- OWLv2 base model for use with Autodistill.
autodistill-efficientsam
PublicEfficientSAM base model for use with Autodistill.- YOLO World base module for use with Autodistill.
- YOLO-NAS module for use with Autodistill.
autodistill-qwen-vl
PublicQwen-VL base model for use with Autodistill.