SQ

SqueezeAILab/SqueezeLLM

[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization

717 50 +0/wk
GitHub
efficient-inference large-language-models llama llm localllm model-compression natural-language-processing post-training-quantization quantization small-models text-generation transformer
Trend 0

Star & Fork Trend (22 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

SqueezeAILab/SqueezeLLM has +0 stars this period . Velocity data will be available after more historical data is collected.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric SqueezeLLM MARS autocontext InstructIR
Stars 717 717716718
Forks 50 495145
Weekly Growth +0 -1+10+0
Language Python PythonPythonJupyter Notebook
Sources 1 111
License MIT Apache-2.0Apache-2.0MIT

Capability Radar vs MARS

SqueezeLLM
MARS
Maintenance Activity 0

Last code push 604 days ago.

Community Engagement 35

Fork-to-star ratio: 7.0%. Lower fork ratio may indicate passive usage.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.