latexgen-models

LatexGen model weights (ONNX)

The three ONNX models that LatexGen serves to the browser. LatexGen converts English math and equation screenshots into LaTeX entirely on-device, with nothing leaving the tab.

They are hosted here rather than in the application repository so a clone does not pull 1.6 GB of weights. Each model ships in several precisions plus pre-compressed .gz copies, so a static host can serve whichever the device can run.

Contents

Each directory also carries its tokenizer and config. compressed.json lists which files have a pre-built .gz sibling.

How they are used

LatexGen walks a ladder and only climbs when the previous tier's output fails validation. Texo reads an image first and Texify takes over when Texo's output fails a syntax check or spells out prose. IntelliTeX handles single-line text input before any language model is loaded. Measured on an Apple M5 Pro:

The int4 variants are GPU-only: on CPU, int4 measured about ten times slower than int8, so the application selects int8 there.

LatexGen downloads a directory, serves it from its own static host, and loads it with transformers.js as a local model:

import { pipeline, env } from "@huggingface/transformers";

env.allowRemoteModels = false;
env.allowLocalModels  = true;
env.localModelPath    = "/models/";        // holds intellitex/, texo/, texify/

const specialist = await pipeline("text2text-generation", "intellitex", { dtype: "q8" });
const out = await specialist(
  "Convert natural-language math into a STRICT LaTeX equation\nx squared plus one",
  { max_new_tokens: 64 },
);

Use dtype: "q4" for the int4 weights where WebGPU is available.

For the routing rules, the validation and repair loop, and the benchmarks behind every choice: https://github.com/OlehZhyhinas/LatexGen

---

Published by Oleh Zhyhinas (GitHub, LinkedIn).