Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
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Updated
Jun 17, 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.
Serving YOLOv8 detection model with tf-serving
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.
Tools and experiments for converting Human Activity Recognition (HAR) models to TensorFlow Lite for efficient on-device inference on mobile and wearable devices.
Objective of this repo is to help under understand ONNX and ONNX runtime and how it can plugged in your project for deploying your custom trained model on different platforms.
Model operations workspace discover models, explore datasets, and fine tune with LoRA/QLoRA
The Json.NET Interface Converter/Mapper is a JsonConverter attribute that allows interfaces to be mapped to concrete implementations of those interfaces for use when deserializing an object.
Wrapture lets you go from a Python-trained model to deployable JavaScript with a single command. It generates TypeScript bindings and a Web/Node-compatible wrapper, using WebGPU/WASM-ready ONNX runtimes.
This project allows you to convert Llama model weights to the Hugging Face format, making it easier to work with Llama models in various applications.
Convert ONNX models to NCNN, MNN, TNN, TFLite, PaddleLite — entirely in your browser using WebAssembly. No server, no uploads.
TensorFence is a contract-first diagnostics toolkit for YOLO/PP -> ONNX -> RKNN pipelines, built to catch preprocessing, decode, NMS, and quantization drift before deployment results go bad.
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