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Supported Models

Our goal is for autodistill to support using all foundation models as Base Models and most SOTA supervised models as Target Models. We focused on object detection and segmentation tasks first but plan to launch classification support soon! In the future, we hope autodistill will also be used for models beyond computer vision.

  • ✅ - complete (click row/column header to go to repo)
  • 🚧 - work in progress

object detection

base / target YOLOv8 YOLO-NAS YOLOv5 DETR YOLOv6 YOLOv7 MT-YOLOv6
DETIC 🚧
GroundedSAM 🚧
GroundingDINO 🚧
OWL-ViT 🚧
SAM-CLIP 🚧
LLaVA-1.5 🚧
Kosmos-2 🚧
OWLv2 🚧
Roboflow Universe Models (50k+ pre-trained models) 🚧
CoDet 🚧
VLPart 🚧
Azure Custom Vision 🚧
AWS Rekognition 🚧
Google Vision 🚧

instance segmentation

base / target YOLOv8 YOLO-NAS YOLOv5 YOLOv7 Segformer
GroundedSAM 🚧 🚧
SAM-CLIP 🚧 🚧
SegGPT 🚧 🚧
FastSAM 🚧 🚧 🚧

classification

base / target ViT YOLOv8 YOLOv5
CLIP 🚧
MetaCLIP 🚧
DINOv2 🚧
BLIP 🚧
ALBEF 🚧
FastViT 🚧
AltCLIP 🚧
Fuyu 🚧 🚧 🚧
Open Flamingo 🚧 🚧 🚧
GPT-4
PaLM-2

Roboflow Model Deployment Support

You can optionally deploy some Target Models trained using Autodistill on Roboflow. Deploying on Roboflow allows you to use a range of concise SDKs for using your model on the edge, from roboflow.js for web deployment to NVIDIA Jetson devices.

The following Autodistill Target Models are supported by Roboflow for deployment:

model name Supported?
YOLOv8 Object Detection
YOLOv8 Instance Segmentation
YOLOv5 Object Detection
YOLOv5 Instance Segmentation
YOLOv8 Classification