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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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base_model: |
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- prithivMLmods/Qwen2-VL-OCR-2B-Instruct |
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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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- VQA |
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- Messy Handwriting OCR |
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- OCR |
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- code |
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--- |
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# **Qwen2-VL-OCR-2B-Instruct-GGUF [ VL / OCR ]** |
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> The **Qwen2-VL-OCR-2B-Instruct** model is a fine-tuned version of Qwen/Qwen2-VL-2B-Instruct, tailored for tasks that involve Optical Character Recognition (OCR), image-to-text conversion, math problem solving with LaTeX formatting and Messy Handwriting OCR. This model integrates a conversational approach with visual and textual understanding to handle multi-modal tasks effectively. |
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--- |
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## Model Files (Qwen2-VL-OCR-2B-Instruct, GGUF) |
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| File Name | Size | Quantization | Format | Description | |
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| -------------------------------------- | ------- | ------------ | ------ | ----------------------------- | |
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| `Qwen2-VL-OCR-2B-Instruct.f16.gguf` | 3.09 GB | FP16 | GGUF | Full precision (float16) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q2_K.gguf` | 676 MB | Q2\_K | GGUF | 2-bit quantized | |
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| `Qwen2-VL-OCR-2B-Instruct.Q3_K_L.gguf` | 880 MB | Q3\_K\_L | GGUF | 3-bit quantized (K L variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q3_K_M.gguf` | 824 MB | Q3\_K\_M | GGUF | 3-bit quantized (K M variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q3_K_S.gguf` | 761 MB | Q3\_K\_S | GGUF | 3-bit quantized (K S variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q4_K_M.gguf` | 986 MB | Q4\_K\_M | GGUF | 4-bit quantized (K M variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q4_K_S.gguf` | 940 MB | Q4\_K\_S | GGUF | 4-bit quantized (K S variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q5_K_M.gguf` | 1.13 GB | Q5\_K\_M | GGUF | 5-bit quantized (K M variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q5_K_S.gguf` | 1.1 GB | Q5\_K\_S | GGUF | 5-bit quantized (K S variant) | |
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| `Qwen2-VL-OCR-2B-Instruct.Q6_K.gguf` | 1.27 GB | Q6\_K | GGUF | 6-bit quantized | |
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| `Qwen2-VL-OCR-2B-Instruct.Q8_0.gguf` | 1.65 GB | Q8\_0 | GGUF | 8-bit quantized | |
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--- |
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## i1 Quantized Variants |
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| File Name | Size | Quantization | Description | |
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| ------------------------------------------ | ------- | ------------ | --------------------------------------- | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ1_M.gguf` | 464 MB | i1-IQ1\_M | i1 1-bit medium | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ1_S.gguf` | 437 MB | i1-IQ1\_S | i1 1-bit small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ2_M.gguf` | 601 MB | i1-IQ2\_M | i1 2-bit medium | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ2_S.gguf` | 564 MB | i1-IQ2\_S | i1 2-bit small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ2_XS.gguf` | 550 MB | i1-IQ2\_XS | i1 2-bit extra small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ2_XXS.gguf` | 511 MB | i1-IQ2\_XXS | i1 2-bit extra extra small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ3_M.gguf` | 777 MB | i1-IQ3\_M | i1 3-bit medium | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ3_S.gguf` | 762 MB | i1-IQ3\_S | i1 3-bit small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ3_XS.gguf` | 732 MB | i1-IQ3\_XS | i1 3-bit extra small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ3_XXS.gguf` | 669 MB | i1-IQ3\_XXS | i1 3-bit extra extra small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ4_NL.gguf` | 936 MB | i1-IQ4\_NL | i1 4-bit with no-layernorm quantization | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-IQ4_XS.gguf` | 896 MB | i1-IQ4\_XS | i1 4-bit extra small | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-Q4_0.gguf` | 938 MB | i1-Q4\_0 | i1 4-bit traditional quant | |
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| `Qwen2-VL-OCR-2B-Instruct.i1-Q4_1.gguf` | 1.02 GB | i1-Q4\_1 | i1 4-bit traditional variant | |
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--- |
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## Metadata |
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| File Name | Size | Description | |
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| ---------------- | ------- | --------------------- | |
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| `.gitattributes` | 3.37 kB | Git LFS tracking file | |
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| `config.json` | 34 B | Config placeholder | |
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| `README.md` | 672 B | Model readme | |
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--- |
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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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| Link | Type | Size/GB | Notes | |
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|:-----|:-----|--------:|:------| |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q2_K.gguf) | Q2_K | 0.4 | | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_S.gguf) | Q3_K_S | 0.5 | | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_M.gguf) | Q3_K_M | 0.5 | lower quality | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q3_K_L.gguf) | Q3_K_L | 0.5 | | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.IQ4_XS.gguf) | IQ4_XS | 0.6 | | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q4_K_S.gguf) | Q4_K_S | 0.6 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q4_K_M.gguf) | Q4_K_M | 0.6 | fast, recommended | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_S.gguf) | Q5_K_S | 0.6 | | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q5_K_M.gguf) | Q5_K_M | 0.7 | | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q6_K.gguf) | Q6_K | 0.7 | very good quality | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.Q8_0.gguf) | Q8_0 | 0.9 | fast, best quality | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-0.6B-GGUF/resolve/main/Qwen3-0.6B.f16.gguf) | f16 | 1.6 | 16 bpw, overkill | |
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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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