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richardyoung/Unlimited-OCR-GGUF overview

Unlimited OCR GGUF GGUF quantizations of baidu/Unlimited OCR https://huggingface.co/baidu/Unlimited OCR with its vision projector, for llama.cpp and Ollama. Wh…

ggufllama.cppollamavisionmultimodalocrimage-text-to-textbase_model:baidu/Unlimited-OCRbase_model:quantized:baidu/Unlimited-OCRlicense:mitendpoints_compatibleregion:usconversational

Runs locally from ~787.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
image-text-to-text

Repository Files & Downloads

3 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Unlimited-OCR-Q4_K_M.ggufGGUFQ4_K_M1.82 GBDownload
Unlimited-OCR-Q8_0.ggufGGUFQ8_02.91 GBDownload
mmproj-Unlimited-OCR-F16.ggufGGUFF16787.0 MBDownload

Model Details

Model IDrichardyoung/Unlimited-OCR-GGUF
Authorrichardyoung
Pipelineimage-text-to-text
Licensemit
Base modelbaidu/Unlimited-OCR
Last modified2026-09-29T01:35:44.000Z

Model README

---

base_model: baidu/Unlimited-OCR

base_model_relation: quantized

license: mit

pipeline_tag: image-text-to-text

tags: [gguf, llama.cpp, ollama, vision, multimodal, ocr]

---

Unlimited-OCR-GGUF

GGUF quantizations of baidu/Unlimited-OCR with its vision projector, for llama.cpp and Ollama.

What it outputs: Unlimited-OCR is a document-layout OCR model. It returns each text region with its type and a bounding box, e.g. title [34, 88, 370, 172]INVOICE 4471, and marks pictures as image [x1, y1, x2, y2] regions instead of describing them. Use a general vision model for image descriptions.

| File | What |

|---|---|

| Unlimited-OCR-Q4_K_M.gguf | Language model, Q4_K_M (recommended) |

| Unlimited-OCR-Q8_0.gguf | Language model, Q8_0 |

| mmproj-Unlimited-OCR-F16.gguf | Vision projector (f16), required for images |

Ollama

ollama run richardyoung/unlimited-ocr

Tags: Q4_K_M (default, latest), Q8_0. Image input works in the CLI (drag in a file path) and via the API images field.

llama.cpp

llama-mtmd-cli -m Unlimited-OCR-Q4_K_M.gguf --mmproj mmproj-Unlimited-OCR-F16.gguf --image page.png -p "Transcribe all the text in this image."

Verified

Tested before upload through Ollama with a synthetic invoice and a shapes image (Q4_K_M shown):

  • Invoice transcription: 'title [34, 88, 370, 172]INVOICE 4471 / text [34, 249, 317, 309]Date: 2026-09-28 / text [34, 362, 418, 432]Widgets x3 $42.00 / text [34, 487, 384, 573]TOTAL: $86.20'
  • Shapes: 'image [90, 301, 382, 752] image [513, 301, 816, 752]'

Converted with llama.cpp convert_hf_to_gguf.py (text and --mmproj), quantized with llama-quantize.

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