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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
CAI NEURAL API - Pascal based deep learning neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.
| Date | Stars |
|---|---|
| 2026-07-31 | 432 |
| 2026-08-06 | 432 |
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# CAI NEURAL API [](https://github.com/joaopauloschuler/neural-api/releases) <img align="right" src="docs/cai.png" height="192"> **Everyone says Pascal died in the 90s.** Meanwhile, this Pascal library runs GPT-style transformers, Mixture-of-Experts, RWKV, xLSTM, spiking neurons, and normalizing flows, natively, with no Python nor CUDA lock-in. Your PyTorch project: 4GB of dependencies, a conda environment that breaks monthly. This: **compile to a single native binary with AVX**. This is deep learning the way systems programmers wish it worked. **And it actually runs the real thing.** Point the [`ChatTerminal`](examples/ChatTerminal) example at a HuggingFace instruct model — Qwen2.5 (0.5B up to 32B), Qwen3, Llama (TinyLlama, SmolLM2), Mistral 7B, Phi-3-mini or the OLMoE Mixture-of-Experts — and chat with a genuine LLM in your terminal: **OpenCL-accelerated**, **no Python**, **no CUDA** — with more architectures landing all the time. Then hand a text prompt to [`MusicGenText`](examples/MusicGenText) and watch the *same library* turn *"lo-fi hip-hop with a mellow piano"* into actual audio — T5 encoder and MusicGen decoder. One native binary, from a 20-line CIFAR demo to a billion-parameter transformer. CAI NEURAL API is a Pascal deep-learning library optimized for the AVX, AVX2 and AVX512 instruction sets and for OpenCL devices from AMD, Intel and NVIDIA. Tested on Windows and Linux. ## Highlights * 🗣️ **Run real LLMs, natively** — import a HuggingFace instruct checkpoint (Qwen2.5/Qwen3, Llama, Mistral, Phi-3, OLMoE) and chat from your terminal with [`ChatTerminal`](examples/ChatTerminal). No Python, no CUDA. * 🎵 **Text-to-music** — turn a text prompt into audio with [`MusicGenText`](examples/MusicGenText) (T5 encoder + MusicGen decoder). * 🔊 **More audio** — separate a song into stems with [`MusicSourceSeparation`](examples/MusicSourceSeparation), or talk to an audio-aware model with [`Qwen2AudioChat`](examples/Qwen2AudioChat). * 🧠 **Modern architectures, built in** — GPT-style transformers, Mixture-of-Experts, RWKV, xLSTM, spiking neurons and normalizing flows, all as native Pascal layers. * 🖼️ **Image super-resolution** — upscale images with a trained network via the [`SuperResolution`](examples/SuperResolution) command-line tool (ships with a ready-to-use model). * ⚡ **Fast everywhere** — AVX/AVX2/AVX512 CPU paths plus OpenCL offload for AMD, Intel and NVIDIA GPUs. * 📦 **Single-binary deploy** — compile to one self-contained native executable. No runtime, no dependency tree. * 📖 **Readable at native speed** — clean, easy-to-learn Pascal that compiles to fast native code. No trade-off between readable source and raw performance. ## Prerequisites You'll need [Lazarus](https://www.lazarus-ide.org/) development environment. If you have an OpenCL capable device, you'll need its OpenCL drivers. Many examples use the [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. You'll also find examples for the [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html), [MNIST](http://yann.lecun.com/exdb/mnist/), [Fashion MNIST](https://www.kaggle.com/zalando-research/fashionmnist) and the [Places365-Standard Small images 256x256](http://places2.csail.mit.edu/download.html) dataset. ## Will It Work with Delphi? This project is [Lazarus](https://www.lazarus-ide.org/) / [Free Pascal](https://www.freepascal.org/) based. The master branch does not work with Delphi. For Delphi, use [v2.0.0](https://github.com/joaopauloschuler/neural-api/releases/tag/v2.0.0) instead. ## Installation Clone this project, add the [**neural**](https://github.com/joaopauloschuler/neural-api/tree/master/neural) folder to your [Lazarus](https://www.lazarus-ide.org/) unit search path and you'll be ready to go! ## A.I. Powered Support You can get A.I. powered help from these tools: * [CAI Neural API support at Poe (free)](https://poe.com/CAI-NEURAL-API-FREE) * [CAI Neur
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:cc59ed8f3a11f106, llm:Description and topics: 'Pascal based deep learning neural network API', topics include 'machine-learning-api', 'pascal-neural-network', 'pascal-ai', 'pascal-artificial-intelligence', 'cifar-10' and references to AVX/OpenCL optimization.
matched fp:cc59ed8f3a11f106, llm:Description and topics: 'Pascal based deep learning neural network API', topics include 'machine-learning-api', 'pascal-neural-network', 'pascal-ai', 'pascal-artificial-intelligence', 'cifar-10' and references to AVX/OpenCL optimization.
matched fp:cc59ed8f3a11f106, llm:Description and topics: 'Pascal based deep learning neural network API', topics include 'machine-learning-api', 'pascal-neural-network', 'pascal-ai', 'pascal-artificial-intelligence', 'cifar-10' and references to AVX/OpenCL optimization.