--- title: Datasent emoji: 🟪 colorFrom: indigo colorTo: blue sdk: static pinned: true ---

Datasent - Polygen: polynomial tokenization and compression for ML data

Datasent builds **Polygen**, an SDK that tokenizes numeric, image, text, audio, and video data by fitting a compact basis to each window, with a lossless `x = f_x + r` decomposition: the fitted prediction `f_x` plus the residual `r`. The representation is small, structured, and decodes exactly. ## Polygen for Qwen2-VL Our flagship demo applies Polygen to a vision-language model: it compresses the visual tokens Qwen2-VL feeds to the LLM, and a small LoRA adapter teaches the model to read the compressed representation. On ScienceQA the recipe holds or improves accuracy while shrinking the visual sequence: - **+8.4pp accuracy** over the un-spliced baseline at the accuracy tier (T=3) - At the compression tier (T=2, +7.4pp accuracy): **~49% fewer visual tokens** and **~3.7x (nearly 4x) more requests per GPU** in cached serving - **~5x smaller** stored visual representation The vision encoder and LLM weights are otherwise untouched; the compression sits between the merger and the LLM. ## Try it - **[Polygen for Qwen2-VL](https://huggingface.co/spaces/datas3nt/qwen2vl-polygen)** -- upload an image, compare answers with and without compression, scored per image - **[Polygen RAG demo](https://huggingface.co/spaces/datas3nt/qwen2vl-polygen-rag)** -- retrieval over a compressed visual-token corpus - **[Polygen tokenization demo](https://huggingface.co/spaces/datas3nt/polygen-demo)** -- the core tokenizer ## Models - **[qwen2vl-polygen-7b-lora-r16-1000](https://huggingface.co/datas3nt/qwen2vl-polygen-7b-lora-r16-1000)** -- 7B LoRA adapter - **[qwen2vl-polygen-lora-r16-1000](https://huggingface.co/datas3nt/qwen2vl-polygen-lora-r16-1000)** -- 2B LoRA adapter Learn more at [datasent.com](https://www.datasent.com).