1.datalab-to / indra
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
+491 stars
from 1,086 · score 6.20
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8 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
2.ultralytics / yolov5
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
+26 stars
from 58,221 · score 3.30
3.onnx / onnx
Open standard for machine learning interoperability
+17 stars
from 21,617 · score 2.89
4.Megvii-BaseDetection / YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
+9 stars
from 10,675 · score 2.30
5.ultralytics / yolov3
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
+7 stars
from 10,624 · score 2.08
6.llmware-ai / llmware
Unified framework for building enterprise RAG pipelines with small, specialized models
+1 stars
from 14,817 · score 0.69
7.microsoft / MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
+1 stars
from 5,803 · score 0.69
8.gmalivenko / pytorch2keras
PyTorch to Keras model convertor
+1 stars
from 860 · score 0.69