HN · GitHub Signals

OPEN SOURCE, IN FOCUS

bittern

intelchina-ai/bittern

Making 1.58-bit models simple to build and broadly accessible through low-cost, high-accuracy post-training ternary quantization.

Explore on GitHub ↗

Saved projects stay in this browser. No account needed.

TAKE A CLOSER LOOK

Start with the source.

The repository is the place to check installation steps, supported platforms, the license, and current maintenance before choosing a tool.

Read the documentation on GitHub ↗

Keep exploring

Find projects in the same areas, or search the archive for a different approach.

ANOTHER GOOD FIND

Explore related projects

View the archive ↗

Connected by topics and descriptions.

futuremls-lab

oscar

OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization

Take a look →
the-school-of-ai

llm

LightningLM 0.1V — Reference training pipeline for the LightningLM family. 2B dense seed → 5B MoE → 9B MoE → 120B sparse MoE through TurboQuant-PreTraining on a single eight-GPU node. Companion code for *Reversible Foundations*.

Take a look →
aiksa2090

agentic-swarm

🧠 Multi-Agent AI System running 100% offline using Google Gemma-4 models. 5 specialized AI agents collaborate in infinite loops for brainstorming. Features: Dynamic VRAM swapping, 4-bit NF4 quantization, WhatsApp-style RTL UI, live token streaming, AI-powered agent customization. Built with PySide6 + PyTorch + Transformers.

Take a look →