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--- |
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license: apache-2.0 |
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language: |
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- en |
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- zh |
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base_model: |
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- prithivMLmods/docscopeOCR-7B-050425-exp |
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pipeline_tag: image-text-to-text |
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library_name: transformers |
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tags: |
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- text-generation-inference |
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- document |
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- ocr |
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--- |
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# **docscopeOCR-7B-050425-exp-GGUF** |
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> 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. |
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## Model File |
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| File Name | Size | Format | Description | |
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|-----------------------------------------------|---------|----------------|----------------------------------------| |
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| docscopeOCR-7B-050425-exp.IQ4_XS.gguf | 4.25 GB | GGUF (IQ4_XS) | Int4 extra-small quantized model | |
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| docscopeOCR-7B-050425-exp.Q2_K.gguf | 3.02 GB | GGUF (Q2_K) | 2-bit quantized model | |
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| docscopeOCR-7B-050425-exp.Q3_K_L.gguf | 4.09 GB | GGUF (Q3_K_L) | 3-bit large quantized model | |
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| docscopeOCR-7B-050425-exp.Q3_K_M.gguf | 3.81 GB | GGUF (Q3_K_M) | 3-bit medium quantized model | |
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| docscopeOCR-7B-050425-exp.Q3_K_S.gguf | 3.49 GB | GGUF (Q3_K_S) | 3-bit small quantized model | |
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| docscopeOCR-7B-050425-exp.Q4_K_M.gguf | 4.68 GB | GGUF (Q4_K_M) | 4-bit medium quantized model | |
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| docscopeOCR-7B-050425-exp.Q5_K_M.gguf | 5.44 GB | GGUF (Q5_K_M) | 5-bit medium quantized model | |
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| docscopeOCR-7B-050425-exp.Q5_K_S.gguf | 5.32 GB | GGUF (Q5_K_S) | 5-bit small quantized model | |
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| docscopeOCR-7B-050425-exp.Q6_K.gguf | 6.25 GB | GGUF (Q6_K) | 6-bit quantized model | |
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| docscopeOCR-7B-050425-exp.Q8_0.gguf | 8.1 GB | GGUF (Q8_0) | 8-bit quantized model | |
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| config.json | 36 B | JSON | Configuration file | |
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| .gitattributes | 2.25 kB | Text | Git attributes configuration | |
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## Quants Usage |
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) |
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Here is a handy graph by ikawrakow comparing some lower-quality quant |
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types (lower is better): |
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