# OpenBMB/MiniCPM-OCR > MiniCPM-OCR is an open-source OCR model family for parsing Chinese and English documents and PDFs into Markdown or JSON, with a 2B model (Jev) that scores recognition quality per region. - Magnitude: 4.6 out of 10 — Early signal - Stars: 163 total · +32 stars measured 2026-10-28, 13:37–15:56 UTC, ≈ 48 by evening - Star trust: star growth looks organic - Category: Language models · Language: Python · License: Apache-2.0 · Created: 2026-10-27 · Last push: 2026-10-28 - GitHub: https://github.com/OpenBMB/MiniCPM-OCR · Page: https://gitnova.dev/en/r/OpenBMB/MiniCPM-OCR ## Useful for - Parse scanned or photographed PDFs into structured Markdown or JSON. - Run MiniCPM-OCR 1.0 locally via vLLM, SGLang, llama.cpp or Ollama. - Score OCR outputs with Jev to flag regions that need manual review. ## Why it’s here - Star-counter measurements on 2026-10-28 (UTC), 13:37–15:56: 131 → 163 stars (+32). This is the change over that interval. - Estimated end-of-day forecast: about +48 stars, using observed gains and the previous day. - The repository is 1 day old and already has 163 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet. - Top new repositories this week: #127. - About 13 forks a day — people are taking the code. ## Star trust Star growth looks organic. Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer. ## Numbers - Forks: 13 - Issues and pull requests: 19 - Watchers: 1 - Average over the last week: 52 per day - Usual pace: too little history (under two weeks) - Stars in the last hour (measured): 8 - Latest release: sdk-v1.0.2 (2026-10-28) ## Stars per day, last 2 days (oldest → newest, today is partial) 2026-10-27 … 2026-10-28: 55, 32 ## Spotted in now - Top new repositories this week: #127 ## More in this category 1. **togg53192-cmd/jailbreaks** — 7.5 · Breakout · Language models · +1,167 stars measured 2026-10-28, 00:02–15:55 UTC, ≈ 1,686 by evening A collection of 31 system prompts, persona locks, and AGENTS.md files for 25+ models (Claude, Gemini, Grok, GLM, DeepSeek, Kimi, Qwen, Gemma, GPT-OSS). Intended for research on how instruction hierarchies and policy overrides affect model… Full card: https://gitnova.dev/en/r/togg53192-cmd/jailbreaks.md 2. **SoMarkAI/OXR** — 7.2 · Breakout · Language models · Python · +253 stars measured 2026-10-28, 03:32–15:55 UTC, ≈ 413 by evening OXR is an open-source document parsing model that turns PDFs and document images into Markdown or JSON with layout coordinates, recognizing 13 element types such as tables, formulas, chemical structures and code. With 1.3B parameters it… Full card: https://gitnova.dev/en/r/SoMarkAI/OXR.md 3. **NVIDIA/auto-ontology** — 6.1 · Early signal · Language models · Python · +145 stars measured 2026-10-28, 00:02–15:55 UTC, ≈ 212 by evening NVIDIA's Python framework that builds a semantic ontology graph over enterprise metadata, giving LLM agents trusted metric and entity definitions for reliable text-to-SQL. Full card: https://gitnova.dev/en/r/NVIDIA/auto-ontology.md 4. **lyramakesmusic/neuron-explorer** — 5.9 · Peaking · Language models · Python · +92 stars measured 2026-10-28, 00:01–15:55 UTC, ≈ 142 by evening A steering-first neuron explorer for Qwen3.5-4B: it pushes every MLP neuron up and down on prompts, keeps all rollouts, and lays the results out over a 3D view of the model for interpretability research. Full card: https://gitnova.dev/en/r/lyramakesmusic/neuron-explorer.md 5. **baidu/Unlimited-OCR** — 5.7 · Breakout · Language models · Python · +321 stars measured 2026-10-28, 00:02–15:55 UTC, ≈ 485 by evening Baidu's OCR model for document parsing: extracts text from single images, multi-page files and PDFs in one pass, supporting long context up to 32768 tokens. Full card: https://gitnova.dev/en/r/baidu/Unlimited-OCR.md --- Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score. Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast. Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself. Data as of 2026-10-28 16:10 UTC, updated every 30 minutes.