Downloads · 30 days
305
12% of all-time downloads
prithivMLmods/proxima-ocr-d.markdown-post3.0.l-GGUF
proxima-ocr-d.markdown-post3.0.l-GGUF is a image-text-to-text model from prithivMLmods. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
proxima-ocr-d.markdown-post3.0.l is an experimental document AI multimodal model fine-tuned on top of Qwen3-VL-8B-Instruct, optimized for high precision OCR and structured document reconstruction. The model converts d…
Downloads · 30 days
305
12% of all-time downloads
All-time downloads
2.5K
Public
Repo size
44.6 GB
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2
Public
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.gguf44.6 GB · 100%
From the Hugging Face model README
proxima-ocr-d.markdown-post3.0.l is an experimental document AI multimodal model fine-tuned on top of Qwen3-VL-8B-Instruct, optimized for high precision OCR and structured document reconstruction. The model converts documents into Markdown, HTML-Markdown, and hybrid enriched documentation formats capable of embedding inline programming languages and reconstructing complex layouts such as tables, forms, and mathematical content. making it ideal for technical documentation, knowledge extraction, and agentic workflows on moderate hardware. This post-3.0 large variant offers enhanced accuracy over smaller siblings for demanding tasks, supporting efficient scaling via Transformers or vLLM for privacy-focused, local deployment in automated parsing pipelines.
| File Name | Quant Type | File Size | File Link |
|---|---|---|---|
| Proxima-OCR-D.Markdown-Post3.0.l.BF16.gguf | BF16 | 16.4 GB | Download |
| Proxima-OCR-D.Markdown-Post3.0.l.F16.gguf | F16 | 16.4 GB | Download |
| Proxima-OCR-D.Markdown-Post3.0.l.Q8_0.gguf | Q8_0 | 8.71 GB | Download |
| Proxima-OCR-D.Markdown-Post3.0.l.mmproj-bf16.gguf | mmproj-bf16 | 1.16 GB | Download |
| Proxima-OCR-D.Markdown-Post3.0.l.mmproj-f16.gguf | mmproj-f16 | 1.16 GB | Download |
| Proxima-OCR-D.Markdown-Post3.0.l.mmproj-q8_0.gguf | mmproj-q8_0 | 752 MB | Download |
(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):
