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For a convenient overview and download list, visit our model page for this model.
Model source
Source description
static quants of https://huggingface.co/lvyufeng/PaddleOCR-VL-0.9B
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Sources
1 sourceVerified Sep 11
Model artifacts
12 artifactsSource excerpts
2 excerptsIf you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
(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):
image.png
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.
PaddleOCR-VL-0.9B.Q2_K.gguf
gguf · 208 MB · SHA-256 634571bb60fe…7c67 · Hugging Face
--- base_model: lvyufeng/PaddleOCR-VL-0.9B language: - en - zh - multilingual library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - pytorch - transformers - mindspore - mindnlp - ERNIE4.5 - image-to-text - ocr - document-parse - layout - table - formula - chart --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/lvyufeng/PaddleOCR-VL-0.9B <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#PaddleOCR-VL-0.9B-GGUF).*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/main/PaddleOCR-VL-0.9B.Q2_K.gguf) | Q2_K | 0.3 | | | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/main/PaddleOCR-VL-0.9B.Q3_K_S.gguf) | Q3_K_S | 0.3 | | | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/main/PaddleOCR-VL-0.9B.Q3_K_M.gguf) | Q3_K_M | 0.4 | lower quality | | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/main/PaddleOCR-VL-0.9B.Q3_K_L.gguf) | Q3_K_L | 0.4 | | | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/main/PaddleOCR-VL-0.9B.IQ4_XS.gguf) | IQ4_XS | 0.4 | | | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/main/PaddleOCR-VL-0.9B.Q4_K_S.gguf) | Q4_K_S | 0.4 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/PaddleOCR-VL-0.9B-GGUF/resolve/m...
Source context: 371 downloads · 2 likes · Pipeline image-to-text · Library transformers · Repo mradermacher/PaddleOCR-VL-0.9B-GGUF
| IQ4_XS |
| 0.4 |
| GGUF | Q4_K_S | 0.4 | fast, recommended |
| GGUF | Q4_K_M | 0.4 | fast, recommended |
| GGUF | Q5_K_S | 0.4 |
| GGUF | Q5_K_M | 0.4 |
| GGUF | Q6_K | 0.5 | very good quality |
| GGUF | Q8_0 | 0.6 | fast, best quality |
| GGUF | f16 | 1.0 | 16 bpw, overkill |
