HN · GitHub Signals

OPEN SOURCE, IN FOCUS

llm

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*.

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.

cerebrasresearch

reap

REAP: Router-weighted Expert Activation Pruning for SMoE compression

Take a look →
hiyucat

deepseek-v4-pro-flash-desktop-app

deepseek-v4-pro-flash deepseek ai large language model llm mixture of experts moe 1m context window hybrid attention architecture compressed sparse attention csa heavily compressed attention hca manifold constrained hyper deepseek-v4-pro deepseek-v4-flash open source hugging face github repository api access local llm inference vllm ollama

Take a look →
deepseek-ai

deepspec

DeepSpec: a full-stack codebase for training and evaluating speculative decoding algorithms

Take a look →
ferrumox

rabbit

Run Kimi K3 (2.8T MoE) on a 128GB-RAM consumer machine in pure Rust, experts streamed from disk. Tiny engine, immense model.

Take a look →