README.md

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title: README
emoji: 🏢
colorFrom: purple
colorTo: yellow
sdk: docker
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Reuben Data Lab

🏆 Work here was produced for the Uncharted Data Challenge hosted by Adaption Labs — credit to Adaptive Data by Adaption for organizing the hackathon.

Building open, underserved datasets for training and evaluating modern audio, speech, and multimodal models. Every release is open-sourced on Hugging Face with permissive licensing and rich metadata.

Interactive dashboard

An interactive explorer with donut charts, a language Voronoi treemap, and a full dataset breakdown is published as a separate Space:

👉 huggingface.co/spaces/Reubencf/dataset-explorer

Collections

Datasets are grouped into four collections under this org.

• 🎧 Audio — FMA-labeled music, multilingual synthetic TTS, PolyglotAudio.
• 📝 Text — PolyglotText and current-affairs 2023-2026.
• 🖼️ Images — globally-sampled street imagery, multilingual magazine OCR + VQA.
• 💻 Coding — frontend HTML / Tailwind / JS prompts.

The full Adaption-remastered versions live in the Reubencf/proper-adaption collection.

Focus areas

• Under-resourced languages — speech and text coverage beyond English-only datasets.
• Rich supervision — structured metadata per row (genre/mood/BPM/key for music; language/style/voice for speech; geographic and scene classification for imagery), not just raw data + class labels.
• Permissive licensing — Creative Commons, CC-0, MIT where possible.
• Reproducibility — generation pipelines and labeling scripts are open-sourced alongside the data.

Tooling

• Labeling: Google Gemini, Gemma 4 31B via vLLM, Cohere Command R with RAG grounding.
• Speech synthesis: Qwen3-TTS-12Hz-1.7B-Base on 2× H100 with zero-shot voice cloning.
• Remastering: Adaption's Adaptive Data platform.
• Distribution: Hugging Face Hub, with HF Jobs for on-platform data processing.

Contact

• Hugging Face: @Reubencf
• Org home: ReubenDataLab