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README.md

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+---
+license: apache-2.0
+base_model: answerdotai/ModernBERT-base
+tags:
+  - token-classification
+  - compression
+  - context-compression
+  - headroom
+language:
+  - en
+---
+
+# kompress-v3
+
+Token compression classifier fine-tuned from [chopratejas/kompress-v2-base](https://huggingface.co/chopratejas/kompress-v2-base) (ModernBERT-base, 149M params). Trained as part of the [ultrawhale](https://github.com/peterlodri-sec/ultrawhale) fine-tuning loop.
+
+Kompress classifies each token in a message as keep (1) or drop (0). Used by the [headroom proxy](https://github.com/headroomlabs-ai/headroom) to compress LLM context before it reaches the model.
+
+## Eval results (heretic adversarial benchmark)
+
+[Heretic-style prompts](https://github.com/p-e-w/heretic) generate responses maximally dense with must-keep tokens (chemical formulas, CVE identifiers, memory addresses, line numbers). The benchmark measures what fraction of those tokens survive compression.
+
+| Metric | Value |
+|---|---|
+| heretic exact_pct | 0.942 |
+| keep_rate | 0.728 |
+| override_delta | +0.027 |
+| base model | kompress-v2-base |
+
+[Full progression across all versions](https://pocoo.vaked.dev/posts/2026-06-25-kompress-heretic-eval)
+
+## Training
+
+Self-labeled references via kompress-v2-base, 1802 training pairs. mk_in_ref improved from ~0.5 (Q&A labels) to 0.720. First iteration of the ultrawhale self-labeling loop.
+
+## Usage
+
+```python
+# Via headroom proxy (recommended)
+# ANTHROPIC_BASE_URL=http://localhost:8787 claude
+
+# Direct library use
+from headroom import compress, CompressConfig
+result = compress(messages, config=CompressConfig(kompress_model="PeetPedro/kompress-v3"))
+```
+
+## Series
+
+| Version | heretic | keep_rate | Notes |
+|---|---|---|---|
+| v3 | 0.942 | 0.728 | first self-label |
+| v3.1 | 0.925 | — | domain data |
+| v3.2 | 0.929 | — | domain refined |
+| v3.3 | 0.942 | — | domain-only, overfit |
+| **v4** | **0.967** | **0.823** | override internalized |
+| v5 | 0.961 | — | loop converged |
+| **v6** | **0.962** | **0.854** | agent-distribution |
+
+Training code: [ultrawhale](https://github.com/peterlodri-sec/ultrawhale)