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Lightonocr Crispembed GGUF

LightOnOCR-2-1B (LightOn, Apache-2.0): Pixtral ViT (24L, 1024d) + Qwen3 decoder (28L, 1024d). OCR Arena #2. 1B params.

KindOtherVersionRevision 5e95afcBgrade

Model source

Kind
Other
File size
624 MB–2.17 GB
Version
vRevision 5e95afc
Updated
Oct 23, 2026
Downloads
96
Source
Hugging Face

Source description

LightOnOCR-2-1B — CrispEmbed GGUF

LightOnOCR-2-1B (LightOn, Apache-2.0): Pixtral ViT (24L, 1024d) + Qwen3 decoder (28L, 1024d). OCR Arena #2. 1B params.

Files

FileTypeSizeNotes
lightonocr-1b-f16.ggufF162.3 GBFull precision
lightonocr-1b-q8_0.ggufQ8_01.1 GBBest quality quantized
lightonocr-1b-q4_k.ggufQ4_K0.6 GBDesktop/edge target

Usage

# CLI
crispembed --ocr lightonocr-1b-q8_0.gguf image.png

# Server
crispembed-server --ocr lightonocr-1b-q8_0.gguf
curl -X POST http://localhost:8080/math/ocr -d '{'"image": "document.png"}'
from crispembed import CrispMathOcr
ocr = CrispMathOcr("lightonocr-1b-q8_0.gguf")
text = ocr.recognize("document.png")
conf = ocr.mean_confidence
print(f"{text} (confidence: {conf:.2f})")

Source

Provenance and EU AI Act Art. 53 note

  • Upstream model: LightOn/LightOnOCR-2-1B.
  • Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
  • What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
  • Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
  • Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

Sources

1 source
Hugging FacePrimaryVersion 5e95afccf6ae817f8352e0127218a06c02519e5e
huggingface.co/cstr/lightonocr-crispembed-GGUF/tree/5e95afccf6ae817f8352e0127218a06c02519e5e

Verified Oct 23

Model artifacts

3 artifacts

lightonocr-1b-f16.gguf

gguf · 2.17 GB · SHA-256 3b3ee7fa3545…d7a9 · Hugging Face

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lightonocr-1b-q4_k.gguf

gguf · 624 MB · SHA-256 c162d1af62d2…536f · Hugging Face

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lightonocr-1b-q8_0.gguf

gguf · 1.00 GB · SHA-256 3a40ef60d319…1e26 · Hugging Face

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Source excerpts

3 excerpts

--- license: apache-2.0 tags: - ocr - gguf - crispembed - lightonocr pipeline_tag: image-to-text --- # LightOnOCR-2-1B — CrispEmbed GGUF LightOnOCR-2-1B (LightOn, Apache-2.0): Pixtral ViT (24L, 1024d) + Qwen3 decoder (28L, 1024d). OCR Arena #2. 1B params. ## Files | File | Type | Size | Notes | |------|------|------|-------| | lightonocr-1b-f16.gguf | F16 | 2.3 GB | Full precision | | lightonocr-1b-q8_0.gguf | Q8_0 | 1.1 GB | Best quality quantized | | lightonocr-1b-q4_k.gguf | Q4_K | 0.6 GB | Desktop/edge target | ## Usage ```bash # CLI crispembed --ocr lightonocr-1b-q8_0.gguf image.png # Server crispembed-server --ocr lightonocr-1b-q8_0.gguf curl -X POST http://localhost:8080/math/ocr -d '{'"image": "document.png"}' ``` ```python from crispembed import CrispMathOcr ocr = CrispMathOcr("lightonocr-1b-q8_0.gguf") text = ocr.recognize("document.png") conf = ocr.mean_confidence print(f"{text} (confidence: {conf:.2f})") ``` ## Source - Original: [LightOn/LightOnOCR-2-1B](https://huggingface.co/LightOn/LightOnOCR-2-1B) - Converted with CrispEmbed `convert-lightonocr-to-gguf.py` ## Provenance and EU AI Act Art. 53 note - **Upstream model:** [LightOn/LightOnOCR-2-1B](https://huggingface.co/LightOn/LightOnOCR-2-1B). - **Upstream licence:** `apache-2.0`. This repository redistributes under the same terms; it grants no rights the upstream licence does not. - **What was done here:** format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs. - **Training data:** documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. - **Provider status:** under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.

Source context: 96 downloads · 0 likes · Pipeline image-to-text · Repo cstr/lightonocr-crispembed-GGUF

Source context: 58 downloads · 0 likes · Pipeline image-to-text · Repo cstr/lightonocr-crispembed-GGUF