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pypi.org : autodistill-otter

Images to inference with no labeling (use foundation models to train supervised models).

Registry - Source - Documentation - JSON
purl: pkg:pypi/autodistill-otter
Keywords: auto-labeling, computer-vision, deep-learning, foundation-models, grounding-dino, image-annotation, image-classification, instance-segmentation, labeling-tool, machine-learning, model-distillation, multimodal, object-detection, pytorch, segment-anything, yolov5, yolov8
License: MIT
Latest release: 12 months ago
First release: 12 months ago
Downloads: 23 last month
Stars: 1,566 on GitHub
Forks: 122 on GitHub
Total Commits: 194
Committers: 11
Average commits per author: 17.636
Development Distribution Score (DDS): 0.294
More commit stats: commits.ecosyste.ms
See more repository details: repos.ecosyste.ms
Last synced: 16 days ago

autodistill-efficientsam 0.1.0
EfficientSAM model for use with Autodistill
1 version - Latest release: 4 months ago - 1 dependent package - 58 downloads last month - 1,566 stars on GitHub - 2 maintainers
Top 4.3% on pypi.org
autodistill 0.1.26
Distill large foundational models into smaller, domain-specific models for deployment
29 versions - Latest release: 4 months ago - 39 dependent packages - 2 dependent repositories - 6.55 thousand downloads last month - 1,566 stars on GitHub - 3 maintainers
autodistill-bioclip 0.1.0
BioCLIP model for use with Autodistill
1 version - Latest release: 4 months ago - 17 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-blip 0.1.3
BLIP module for use with Autodistill
5 versions - Latest release: 6 months ago - 1 dependent package - 79 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-remote-clip 0.1.2
Remote CLIP model for use with Autodistill
3 versions - Latest release: 6 months ago - 34 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-llava 0.1.0
LLaVA for use with Autodistill
1 version - Latest release: 8 months ago - 54 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-albef 0.1.0
ALBEF module for use with Autodistill
1 version - Latest release: 11 months ago - 30 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-tag2text 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 31 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-open-flamingo 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 26 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-yolov9 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 36 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-yolov4 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 28 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-efficientnet 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 26 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-swinv2 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 30 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-swin 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 19 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-oneformer 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 24 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-coca 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 22 downloads last month - 1,519 stars on GitHub - 2 maintainers
autodistill-glip 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 24 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-chameleon 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 26 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-deta 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 27 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-llama 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 29 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-flan 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 25 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-yolor 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 26 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-yolox 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 30 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-yolov6 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 24 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-dino 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 25 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-flamingo 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 29 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-palm-e 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 26 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-palm2 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 15 downloads last month - 1,519 stars on GitHub - 2 maintainers
autodistill-palm 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 23 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-vertex 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 30 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-azure 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 32 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-blip2 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 25 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-chat-gpt 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 30 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-gpt5 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 22 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistill-gpt4 0.0.1
Images to inference with no labeling (use foundation models to train supervised models).
1 version - Latest release: 12 months ago - 25 downloads last month - 1,566 stars on GitHub - 2 maintainers
autodistll-grounded-sam 0.0.5
Automatically distill large foundational models into smaller, in-domain models for deployment
1 version - Latest release: about 1 year ago - 10 downloads last month - 1,519 stars on GitHub - 1 maintainer