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docscopeOCR-7B-050425-exp-GGUF
prithivMLmods/docscopeOCR-7B-050425-exp-GGUF
docscopeOCR-7B-050425-exp-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 docscopeOCR-7B-050425-exp model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct, optimized for Document-Level Optical Character Recognition (OCR), long-context vision-language understanding, and accurate im…
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Repo size
48.5 GB
Likes
3
Public
Repo makeup
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.gguf48.5 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 3, 2025
- Updated
- Jun 3, 2025
- SHA
- 5d0bbfe6
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Base models
Model card
From the Hugging Face model README
docscopeOCR-7B-050425-exp-GGUF
The docscopeOCR-7B-050425-exp model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-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 File
| File Name | Size | Format | Description |
|---|---|---|---|
| docscopeOCR-7B-050425-exp.IQ4_XS.gguf | 4.25 GB | GGUF (IQ4_XS) | Int4 extra-small quantized model |
| docscopeOCR-7B-050425-exp.Q2_K.gguf | 3.02 GB | GGUF (Q2_K) | 2-bit quantized model |
| docscopeOCR-7B-050425-exp.Q3_K_L.gguf | 4.09 GB | GGUF (Q3_K_L) | 3-bit large quantized model |
| docscopeOCR-7B-050425-exp.Q3_K_M.gguf | 3.81 GB | GGUF (Q3_K_M) | 3-bit medium quantized model |
| docscopeOCR-7B-050425-exp.Q3_K_S.gguf | 3.49 GB | GGUF (Q3_K_S) | 3-bit small quantized model |
| docscopeOCR-7B-050425-exp.Q4_K_M.gguf | 4.68 GB | GGUF (Q4_K_M) | 4-bit medium quantized model |
| docscopeOCR-7B-050425-exp.Q5_K_M.gguf | 5.44 GB | GGUF (Q5_K_M) | 5-bit medium quantized model |
| docscopeOCR-7B-050425-exp.Q5_K_S.gguf | 5.32 GB | GGUF (Q5_K_S) | 5-bit small quantized model |
| docscopeOCR-7B-050425-exp.Q6_K.gguf | 6.25 GB | GGUF (Q6_K) | 6-bit quantized model |
| docscopeOCR-7B-050425-exp.Q8_0.gguf | 8.1 GB | GGUF (Q8_0) | 8-bit quantized model |
| config.json | 36 B | JSON | Configuration file |
| .gitattributes | 2.25 kB | Text | Git attributes configuration |
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, zh
- Created
- Jun 3, 2025
- Updated
- Jun 3, 2025