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Starlight Prod

Task: Steganography detection (and method / bit-order heads) Architecture: BalancedStarlightDetector (multi-stream CNN + fusion gate) Input streams: pixel, meta, alpha, LSB, palette, format/content features (see GGUF...

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Model source

Kind
Other
File size
3.12–3.16 MB
Version
vRevision d854947
Updated
Oct 10, 2026
Downloads
7
Source
Hugging Face

Source description

Model Card: Starlight Balanced Detector (GGUF)

Model Overview

  • Task: Steganography detection (and method / bit-order heads)
  • Architecture: BalancedStarlightDetector (multi-stream CNN + fusion gate)
  • Input streams: pixel, meta, alpha, LSB, palette, format/content features (see GGUF export docs)
  • Primary artifact: GGUF for Stargate / Trin (Go)

Artifacts (this repo on HF)

FileDescription
starlight.ggufPrimary production weights (GGUF v3 / F32)
starlight_gguf_map.jsonTensor name map and export metadata
README.mdThis model card

Optional secondary (may appear if uploaded): detector_balanced.pth, detector_balanced.onnx.

Inference

Production: load starlight.gguf via Stargate / Trin GGUF path — not Python ONNX as the primary path.

Download:

https://huggingface.co/macroadster/starlight-prod/resolve/main/starlight.gguf
https://huggingface.co/macroadster/starlight-prod/resolve/main/starlight_gguf_map.json

Training

  • Dataset: Combined submissions (grok, gemini, claude, chatgpt, sample, val)
  • Checkpoint: models/detector_balanced.pth (training repo)
  • Export: scripts/export_starlight_gguf.py → models/starlight.gguf
  • Typical recipe: Adam, balanced clean/stego sampling (see training repo trainer.py)

Steganography coverage

  • lsb, alpha, exif, eoi / raw, palette (and related variants in datasets)

Performance

MetricValue
Accuracysee training run / leaderboard
False positive focusbalanced detector design

Update metrics after each publish-worthy training run.

License

  • Model: Apache 2.0
  • Code: see training repository LICENSE

Sources

1 source
Hugging FacePrimaryVersion d854947061cf6cc372af90a97d691b0a3504c4c2
huggingface.co/macroadster/starlight-prod/tree/d854947061cf6cc372af90a97d691b0a3504c4c2

Verified Oct 10

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Model artifacts

2 artifacts

detector_balanced.pth

pth · 3.16 MB · SHA-256 54b4cccdcba6…88be · Hugging Face

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starlight.gguf

gguf · 3.12 MB · SHA-256 1243579c3482…3dc4 · Hugging Face

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Source excerpts

3 excerpts

--- license: apache-2.0 tags: - steganography - steganalysis - gguf - balanced-detector - image-classification - computer-vision - bitcoin library_name: gguf pipeline_tag: image-classification datasets: - custom metrics: - accuracy - f1 - auc --- # Model Card: Starlight Balanced Detector (GGUF) ## Model Overview - **Task**: Steganography detection (and method / bit-order heads) - **Architecture**: `BalancedStarlightDetector` (multi-stream CNN + fusion gate) - **Input streams**: pixel, meta, alpha, LSB, palette, format/content features (see GGUF export docs) - **Primary artifact**: **GGUF** for Stargate / Trin (Go) ## Artifacts (this repo on HF) | File | Description | |------|-------------| | `starlight.gguf` | **Primary** production weights (GGUF v3 / F32) | | `starlight_gguf_map.json` | Tensor name map and export metadata | | `README.md` | This model card | Optional secondary (may appear if uploaded): `detector_balanced.pth`, `detector_balanced.onnx`. ## Inference **Production**: load `starlight.gguf` via **Stargate / Trin** GGUF path — not Python ONNX as the primary path. Download: ``` https://huggingface.co/macroadster/starlight-prod/resolve/main/starlight.gguf https://huggingface.co/macroadster/starlight-prod/resolve/main/starlight_gguf_map.json ``` ## Training - **Dataset**: Combined submissions (grok, gemini, claude, chatgpt, sample, val) - **Checkpoint**: `models/detector_balanced.pth` (training repo) - **Export**: `scripts/export_starlight_gguf.py` → `models/starlight.gguf` - **Typical recipe**: Adam, balanced clean/stego sampling (see training repo `trainer.py`) ## Steganography coverage - `lsb`, `alpha`, `exif`, `eoi` / raw, `palette` (and related variants in datasets) ## Performance | Metric | Value | |--------|-------| | Accuracy | see training run / leaderboard | | False positive focus | balanced detector design | Update metrics after each publish-worthy training run. ## License - Model: Apache 2.0 - Code: see training repository LICENSE

Source context: 7 downloads · 0 likes · Pipeline image-classification · Library gguf · Repo macroadster/starlight-prod

Source context: 41 downloads · 0 likes · Pipeline image-classification · Library gguf · Repo macroadster/starlight-prod