Repository Index

TranslatedChinese LLaMA & Alpaca LLMs + local CPU/GPU training and deployment

• llm
• plm
• pre-trained-language-models
• alpaca

A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.

• avx2
• c99
• cpu-inference
• deep-learning

Open-source library of optimized deep learning operations (matmul, convolution, attention) for CPUs (x64, AArch64, RISC-V) and Intel GPUs. Used by PyTorch, TensorFlow, OpenVINO, and ONNX Runtime.

• onednn
• oneapi
• performance
• cpp

The Swiss Army Knife of Offline AI. Chat, see, speak, and generate images on your phone or Mac — GGUF LLMs, vision, Whisper speech-to-text, Stable Diffusion, tool calling, and local-network servers. Runs on your CPU, GPU, or NPU. No account, no API key, zero data leaves your device.

• privacy-first
• gguf
• llama-cpp
• local-ai

1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy

• ai
• cpu
• document-parsing
• ocr

A computer, compiled into the weights of a language model. An exact CPU inside Qwen3.5-4B, with Gated DeltaNet state as RAM.

• gated-deltanet
• interpretability
• llm
• qwen

37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.

• avx2
• c
• cpu-inference
• gguf

Local inference for diffusion language models (LLaDA, Dream), written in Mojo

• cpu
• diffusion-models
• gguf
• inference

One command downloads a complete offline, no-internet emergency library: local AI (CPU/GPU), document Q&A, full Wikipedia, offline maps for any country/region (default US), survival/repair/medical archives, and public-domain manuals. Asks only where to save.

• claude
• claude-code
• emergency-preparedness
• kiwix

Spends CPU cycles so you don't spend tokens. The LLM gets a briefing packet instead of a flashlight in a dark room.