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visionOCR-3B-061125-GGUF
prithivMLmods/visionOCR-3B-061125-GGUF
visionOCR-3B-061125-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.
The visionOCR-3B-061125 model is a fine-tuned version of Qwen/Qwen2.5-VL-3B-Instruct, optimized for Document-Level Optical Character Recognition (OCR), long-context vision-language understanding, and accurate image-to…
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Repo size
17.2 GB
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4
Public
Repo makeup
Click a slice to open those files.
.gguf17.2 GB · 100%
At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- apache-2.0
- Model type
- qwen2_5_vl
- Access
- Public
- Created
- Jun 12, 2025
- Updated
- Jun 16, 2025
- SHA
- 7095e635
Try a prompt
Base models
Model card
From the Hugging Face model README
visionOCR-3B-061125-GGUF
The visionOCR-3B-061125 model is a fine-tuned version of Qwen/Qwen2.5-VL-3B-Instruct, optimized for Document-Level Optical Character Recognition (OCR), long-context vision-language understanding, and accurate image-to-text conversion with mathematical LaTeX formatting. Built on top of the Qwen2.5-VL architecture, this model significantly improves document comprehension, structured data extraction, and visual reasoning across diverse input formats.
Model Files
| File Name | Size | Format | Description |
|---|---|---|---|
| visionOCR-3B-061125-BF16.gguf | 6.18 GB | BF16 | Brain floating point 16-bit |
| visionOCR-3B-061125-Q6_K.gguf | 2.54 GB | Q6_K | 6-bit quantized |
| visionOCR-3B-061125-Q5_K_M.gguf | 2.22 GB | Q5_K_M | 5-bit quantized, medium quality |
| visionOCR-3B-061125-Q4_K_M.gguf | 1.93 GB | Q4_K_M | 4-bit quantized, medium quality |
| visionOCR-3B-061125-Q3_K_M.gguf | 1.59 GB | Q3_K_M | 3-bit quantized, medium quality |
| visionOCR-3B-061125-Q3_K_S.gguf | 1.45 GB | Q3_K_S | 3-bit quantized, small quality |
| visionOCR-3B-061125-Q2_K.gguf | 1.27 GB | Q2_K | 2-bit quantized |
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):
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- qwen2_5_vl
- License
- apache-2.0
- Languages
- en
- Created
- Jun 12, 2025
- Updated
- Jun 16, 2025