Dynamic markdowns
Collection
Document-AI, HTML, OCR
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4 items
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Updated
epsilon-ocr-d.markdown-post3.0.m-GGUF
epsilon-ocr-d.markdown-post3.0.m is an experimental document AI multimodal model fine tuned on top of Qwen2.5-VL-3B-Instruct, optimized for OCR driven document reconstruction and dynamic Markdown generation. It converts documents into structured Markdown, HTML-Markdown, and hybrid technical documentation formats with inline code adaptation. Built for efficient model scaling, it offers strong performance with reduced compute requirements. This post-3.0 iteration enhances accuracy in reading order detection, element localization, and multimodal reasoning for real-world PDFs/images, positioning it as a lightweight alternative for privacy-focused, local deployment in document parsing pipelines.
Epsilon-OCR-D.Markdown-Post3.0.m [GGUF]
| File Name | Quant Type | File Size | File Link |
|---|---|---|---|
| Epsilon-OCR-D.Markdown-Post3.0.m.BF16.gguf | BF16 | 6.18 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.F16.gguf | F16 | 6.18 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.F32.gguf | F32 | 12.3 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.Q8_0.gguf | Q8_0 | 3.29 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.mmproj-bf16.gguf | mmproj-bf16 | 1.34 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.mmproj-f16.gguf | mmproj-f16 | 1.34 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.mmproj-f32.gguf | mmproj-f32 | 2.67 GB | Download |
| Epsilon-OCR-D.Markdown-Post3.0.m.mmproj-q8_0.gguf | mmproj-q8_0 | 848 MB | Download |
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):
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Model tree for prithivMLmods/epsilon-ocr-d.markdown-post3.0.m-GGUF
Base model
Qwen/Qwen2.5-VL-3B-Instruct