Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
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Updated
Sep 12, 2026 - Python
Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
Pytorch to Keras/Tensorflow/TFLite conversion made intuitive
Convert 3d model (STL/IGES/STEP/OBJ/FBX) to gltf and compression
Gradio based tool to run opensource LLM models directly from Huggingface
A practical lab for exploring Apple's Core AI framework, model assets, specialization, and on-device inference.
Automated converter for ONNX models (particularly ESRGAN) to RKNN format for Rockchip NPUs. Features include Docker-based conversion and GitHub Actions automation.
A flexible utility for converting tensor precision in PyTorch models and safetensors files, enabling efficient deployment across various platforms.
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.
A general-purpose ONNX → TFLite compiler built on MLIR, producing native TensorFlow Lite FlatBuffers.
Serving YOLOv8 detection model with tf-serving
Tests whether ML models preserve their behavior after conversion, quantization, or other transformations.
Transpile PyTorch modules to runnable JAX or MLX artifacts through ONNX, generating backend Python code and weights.
This project demonstrates how to download a model from Hugging Face, convert it to GGUF format, and upload it back to Hugging Face using a Colab notebook.
This sample shows how to convert TensorFlow model to OpenVINO IR model and how to quantize OpenVINO model.
MLX Porting Toolkit — an agent-guided, evidence-gated pipeline (scaffold → convert → parity → benchmark) plus a portable skill for porting PyTorch/Hugging Face models to Apple MLX.
UMC — The ffmpeg of AI models. Convert any model format to any other format (GGUF, ONNX, SafeTensors, CoreML, TensorRT...) without quality loss, at maximum speed, with mathematical proof. Built in Rust.
Open-source CPU inference and PyTorch tools for Needle 2: CQ2/CQ4 quantization, model conversion, QAT, and ARM NEON/SDOT kernels.
Convert ONNX models to NCNN, MNN, TNN, TFLite, PaddleLite — entirely in your browser using WebAssembly. No server, no uploads.
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