| | --- |
| | license: apache-2.0 |
| | base_model: |
| | - FireRedTeam/FireRed-OCR |
| | language: |
| | - en |
| | pipeline_tag: image-text-to-text |
| | library_name: transformers |
| | tags: |
| | - text-generation-inference |
| | - llama.cpp |
| | --- |
| | |
| | # **FireRed-OCR-GGUF** |
| |
|
| | > FireRed-OCR from FireRedTeam is a specialized framework that transforms general Large Vision-Language Models into pixel-precise structural document parsing experts, tackling "Structural Hallucination" issues like disordered rows and invented formulas through a shift to "structural engineering" paradigms, achieving SOTA 92.94% on OmniDocBench v1.5—vastly outperforming DeepSeek-OCR 2, OCRVerse, and giants like Gemini-3.0 Pro or Qwen3-VL-235B. Its key innovations include Format-Constrained GRPO (Group Relative Policy Optimization) for enforcing syntactic validity (no unclosed tables or invalid LaTeX), a "Geometry + Semantics" data factory with geometric clustering and multi-dimensional tagging for balanced long-tail layouts, and a progressive pipeline: multi-task pre-alignment for spatial grounding, specialized SFT for standardized full-image Markdown output, and GRPO self-correction via RL. Demonstrating in-the-wild robustness on FireRedBench complex layouts over traditional systems like PaddleOCR, it excels in high-fidelity parsing of tables, equations, forms, and multi-column documents for real-world automation. |
| |
|
| | ## Model Files |
| |
|
| | | File Name | Quant Type | File Size | File Link | |
| | | - | - | - | - | |
| | | FireRed-OCR.BF16.gguf | BF16 | 3.45 GB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.BF16.gguf) | |
| | | FireRed-OCR.F16.gguf | F16 | 3.45 GB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.F16.gguf) | |
| | | FireRed-OCR.F32.gguf | F32 | 6.89 GB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.F32.gguf) | |
| | | FireRed-OCR.Q8_0.gguf | Q8_0 | 1.83 GB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.Q8_0.gguf) | |
| | | FireRed-OCR.mmproj-bf16.gguf | mmproj-bf16 | 823 MB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.mmproj-bf16.gguf) | |
| | | FireRed-OCR.mmproj-f16.gguf | mmproj-f16 | 823 MB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.mmproj-f16.gguf) | |
| | | FireRed-OCR.mmproj-f32.gguf | mmproj-f32 | 1.63 GB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.mmproj-f32.gguf) | |
| | | FireRed-OCR.mmproj-q8_0.gguf | mmproj-q8_0 | 445 MB | [Download](https://huggingface.co/prithivMLmods/FireRed-OCR-GGUF/blob/main/FireRed-OCR.mmproj-q8_0.gguf) | |
| |
|
| | ## Quants Usage |
| |
|
| | (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
| |
|
| | Here is a handy graph by ikawrakow comparing some lower-quality quant |
| | types (lower is better): |
| |
|
| |  |
