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+LightOnOCR-2-1B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text

LightOnOCR-2-1B-Q4_K_M.gguf

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+version https://git-lfs.github.com/spec/v1
+oid sha256:26cf61864df5b3639d8af791ae418bb59bf94d65b57422f2f174b072ea0ba049
+size 396701312

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model: lightonai/LightOnOCR-2-1B
+tags:
+  - ocr
+  - document-understanding
+  - vision-language
+  - gguf
+  - llama.cpp
+  - multimodal
+language:
+  - en
+  - fr
+  - de
+  - es
+  - it
+  - nl
+  - pt
+  - sv
+  - da
+  - zh
+  - ja
+library_name: gguf
+pipeline_tag: image-text-to-text
+---
+
+# LightOnOCR-2-1B GGUF
+
+GGUF quantized versions of [lightonai/LightOnOCR-2-1B](https://huggingface.co/lightonai/LightOnOCR-2-1B) for use with [llama.cpp](https://github.com/ggml-org/llama.cpp).
+
+## Model Description
+
+LightOnOCR-2-1B is a 1B-parameter end-to-end vision-language model for OCR, converting documents (PDFs, scans, images) into clean, naturally ordered text.
+
+### Highlights
+
+- **Speed:** 3.3× faster than Chandra OCR, 1.7× faster than OlmOCR
+- **Efficiency:** <$0.01 per 1,000 pages on H100
+- **End-to-End:** Fully differentiable, no external OCR pipeline
+- **Versatile:** Handles tables, receipts, forms, multi-column layouts, and math notation
+
+## Available Files
+
+| File | Size | Description |
+|------|------|-------------|
+| `LightOnOCR-2-1B-f16.gguf` | 1.1 GB | Language model (F16, highest quality) |
+| `LightOnOCR-2-1B-Q8_0.gguf` | 610 MB | Language model (Q8_0, near-lossless) |
+| `LightOnOCR-2-1B-Q4_K_M.gguf` | 378 MB | Language model (Q4_K_M, balanced) |
+| `LightOnOCR-2-1B-mmproj-f16.gguf` | 781 MB | Vision encoder + projector (required) |
+
+> **Note:** The vision encoder (`mmproj`) should NOT be quantized as it significantly impacts image understanding quality.
+
+## Usage with llama.cpp
+
+### Build llama.cpp
+
+```bash
+git clone https://github.com/ggml-org/llama.cpp
+cd llama.cpp
+cmake -B build
+cmake --build build --config Release
+```
+
+### Run OCR
+
+```bash
+# Using F16 (highest quality)
+./build/bin/llama-mtmd-cli \
+    -m LightOnOCR-2-1B-f16.gguf \
+    --mmproj LightOnOCR-2-1B-mmproj-f16.gguf \
+    --image your-document.png \
+    -ngl 99 \
+    -c 4096 \
+    -n 1000 \
+    --temp 0.2 \
+    --repeat-penalty 1.15 \
+    --repeat-last-n 128 \
+    -p "OCR this image"
+
+# Using Q4_K_M (smaller, faster)
+./build/bin/llama-mtmd-cli \
+    -m LightOnOCR-2-1B-Q4_K_M.gguf \
+    --mmproj LightOnOCR-2-1B-mmproj-f16.gguf \
+    --image your-document.png \
+    -ngl 99 \
+    -c 4096 \
+    -n 1000 \
+    --temp 0.2 \
+    --repeat-penalty 1.15 \
+    -p "OCR this image"
+```
+
+## Recommended Parameters
+
+| Parameter | Value | Description |
+|-----------|-------|-------------|
+| `--temp` | 0.2 | Official recommended temperature |
+| `--repeat-penalty` | 1.15 | Prevents repetition (1.1-1.2 optimal) |
+| `--repeat-last-n` | 128 | Tokens to consider for penalty |
+| `-n` | 1000 | Max output tokens (avoid >1500) |
+| `-ngl` | 99 | GPU layers (use all for best speed) |
+
+### Parameter Notes
+
+- **repeat-penalty**: Values above 1.2 may reduce OCR quality
+- **-n (max tokens)**: Limiting to ~1000 prevents repetition at end of long documents
+- **Image preprocessing**: Render PDFs to PNG at 1540px longest edge
+
+## Performance (Apple M4 Max)
+
+| Metric | Value |
+|--------|-------|
+| Image encoding | ~435 ms |
+| Image decoding | ~45 ms |
+| Prompt processing | ~1,850 tokens/s |
+| Text generation | ~228 tokens/s |
+| Total time (1000 tokens) | ~8-10 sec |
+
+## Quantization Details
+
+| Format | Bits/Weight | Size Reduction | Quality Impact |
+|--------|-------------|----------------|----------------|
+| F16 | 16 | - | Baseline |
+| Q8_0 | 8 | 45% | Nearly lossless |
+| Q4_K_M | 4.5 | 66% | Minimal |
+
+## Credits
+
+- Original model: [lightonai/LightOnOCR-2-1B](https://huggingface.co/lightonai/LightOnOCR-2-1B)
+- GGUF conversion: Using [llama.cpp](https://github.com/ggml-org/llama.cpp) convert tools
+- Paper: [LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model](https://arxiv.org/pdf/2601.14251)
+
+## License
+
+Apache License 2.0 (same as original model)
+
+## Citation
+
+```bibtex
+@misc{lightonocr2_2026,
+  title        = {LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model for State-of-the-Art OCR},
+  author       = {Said Taghadouini and Adrien Cavaill\`{e}s and Baptiste Aubertin},
+  year         = {2026},
+  howpublished = {\url{https://arxiv.org/pdf/2601.14251}}
+}
+```