MLX: An array framework for Apple silicon
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MLX: An array framework for Apple silicon
Stable Diffusion with Core ML on Apple Silicon
Production ready toolkit to run AI locally
Local speech-to-text for macOS on-device AI, fully private, optional cloud
Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.
Neural Network built in Apple Playground using Swift
BYOK voice recording companion with ASR transcription, speaker diarization, AI summaries, and local ASR endpoint support.
The MobileNet neural network using Apple's new CoreML framework
Imagination Studio by keys+Wasserman powered by TensorFold: an AI film studio for Mac and NVIDIA DGX Spark. Plan a film like a crew (Slate workflow by Sam Wasserman), render Qwen-Image-2.1 / FLUX3-K pictures and MiniMax H3 / FastH3 video with sound on TensorFold.
ilastik-shell, applets, and workflows to string them together.
Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.
🌏 A zero-dependency networking solution for building modern and secure iOS, watchOS, macOS and tvOS applications.
Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.