{"data":{"full_name":"Dimitrios-Kafetzis/EdgeNN","name":"EdgeNN","description":"Lightweight, zero-allocation C11 library for neural network inference on ARM Cortex-M/A microcontrollers. Supports Dense, Conv2D, LSTM, GRU, Multi-Head Attention, and 18 operators total with INT8 quantized and FP32 reference paths. Deterministic execution, no heap, no dependencies.","stars":0.0,"forks":0.0,"language":"C","license":"MIT","archived":0.0,"subcategory":"onnx-model-deployment","last_pushed_at":"2026-02-16T13:33:11+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":10.0,"adoption_score":0.0,"maturity_score":9.0,"community_score":0.0,"quality_score":19.0,"quality_tier":"experimental","risk_flags":"['no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-08T17:13:05.291790+00:00"}}