---
license: apache-2.0
base_model: Qwen/Qwen2-0.5B
tags:
- experimental
- inference
- feature-selection
- bayesian
---
# Adaptive Sparse Feature Selection at Inference Time (Qwen2-0.5B)
**Status: experimental / work in progress.** This is a research test, not a production release, not a compression method, and not a claim of a new architecture. Numbers below are placeholders — real plots and stats will be added once benchmark runs are complete.
## What this actually is
During autoregressive generation, this repo tracks a small set of statistical features (mean, std, quantiles, rolling window stats, autocorrelation — 64 features per layer) computed from the **input activations** hitting each attention/FFN weight matrix in Qwen2-0.5B. A lightweight Bayesian selector then flags which of those features deviate meaningfully from their running distribution at each generation step, instead of treating every feature as equally relevant every time.
The output metric is simple: **w…
