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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.

TipoOtherVersãoRevision 5e95afcBnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
624 MB–2,17 GB
Versão
vRevision 5e95afc
Atualizado
23 de out. de 2026
Downloads
96
Fonte
Hugging Face

Descrição da fonte

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.

Fontes

1 fonte
Hugging FacePrimárioVersão 5e95afccf6ae817f8352e0127218a06c02519e5e
huggingface.co/cstr/lightonocr-crispembed-GGUF/tree/5e95afccf6ae817f8352e0127218a06c02519e5e

Verificado 23 de out.

Artefatos de modelo

3 artefatos

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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Trechos de fonte

3 trechos

--- 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