NVIDIA / Model-Optimizer
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
UditAkhourii / adhd
ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cognitive frames, scores, prunes traps, deepens the survivors. The no-brainer skill for creative and interdisciplinary work.
Tarquinen / opencode-dynamic-context-pruning
Dynamic context pruning plugin for OpenCode - intelligently manages conversation context to optimize token usage
qualcomm / aimet
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
intel / neural-compressor
SOTA low-bit LLM quantization (INT8/FP8/MXFP8/INT4/MXFP4/NVFP4) & sparsity; leading model compression techniques on PyTorch, TensorFlow, and ONNX Runtime
peremartra / Large-Language-Model-Notebooks-Course
Practical course about Large Language Models.
opendilab / LightZero
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)
tensorflow / model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
openvinotoolkit / nncf
Neural Network Compression Framework for enhanced OpenVINO™ inference
MIT-SPARK / KISS-Matcher
KISS-Matcher: Fast, Robust, and Scalable Registration + ROS2 SLAM examples
wolfgarbe / PruningRadixTrie
PruningRadixTrie - 1000x faster Radix trie for prefix search & auto-complete
ZLKong / Awesome-Collection-Token-Reduction
A collection of token reduction (token pruning, merging, clustering, etc.) techniques for ML/AI
PipeNetwork / kimi-k3-mlx
MLX port of moonshotai/Kimi-K3 (2.78T multimodal MoE): streaming converter, REAP expert pruning, and per-language expert-overlap analysis
ranxianglei / billion-context-pi
稳定可用 Use billion-context instead .Active Context Pruning for pi ，100K tokens is enough. ，主动压缩上下文，10w 上下文足矣
Tyan66666 / billion-context-dsh
Model-driven context management (Active Context Pruning / ACP) for the DeepSeek Harness — the model decides when and what to compress. Ported from billion-context-pi (ranxianglei); acp-kernel reused verbatim. CompactionEngine backend with compress/decompress/search_context/acp_status tools.
freeai-org / Scalpel
✂️Scalpel: Recovery-Aware Layer Pruning for Faster Vision-Language Models
ashishsinha1602 / schemagate
Text-to-SQL access control: schema selection that gives the LLM only the tables the caller is allowed to read. Row-level-security-aware table pruning for LangChain, MCP and any SQL agent. Postgres, Oracle, MySQL, SQL Server. 75% fewer prompt tokens.
Sev7eEn7 / dsh-sieve
dsh-sieve: context engineering & token optimization plugin for DeepSeek Harness (DSH) — tool output filtering, context pruning, progressive skill disclosure. 36% smaller payload in offline replay. DSH 上下文管理与 token 优化节省插件。
compozy / yoshi
Context-pruning proxy for Claude Code and Codex: Jev judges which history is still needed, measured not claimed. POC here now, heading soon into https://github.com/compozy/compozy
usamahz / make-your-model-fast
A Systems View of Efficient Machine Learning, from Silicon to Agents. Fourteen parts, from roofline analysis and vector units up through kernels, compilers, quantisation, compression, vision, on-device language models, robotics, profiling, serving and agents.
kimberlyii / Omni-Prune
Query-aware token pruning for efficient OmniLLMs.