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For a convenient overview and download list, visit our model page for this model.
Fonte do modelo
Descrição da fonte
weighted/imatrix quants of https://huggingface.co/nanonets/Nanonets-OCR2-1.5B-exp
For a convenient overview and download list, visit our model page for this model.
static quants are available at
Fontes
1 fonteVerificado 17 de set.
Artefatos de modelo
25 artefatosTrechos de fonte
2 trechosThis is a vision model - mmproj files (if any) will be in the static repository.
If 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)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| GGUF | imatrix | 0.1 | imatrix file (for creating your own quants) |
| GGUF | i1-IQ1_S | 0.4 | for the desperate |
| GGUF | i1-IQ1_M | 0.4 | mostly desperate |
| GGUF | i1-IQ2_XXS | 0.5 | |
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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
Nanonets-OCR2-1.5B-exp.i1-IQ2_M.gguf
gguf · 396 MB · SHA-256 9702baa5cd3b…99f8 · Hugging Face
Nanonets-OCR2-1.5B-exp.i1-IQ2_XXS.gguf
gguf · 347 MB · SHA-256 671085898fd3…5110 · Hugging Face
BaixarNanonets-OCR2-1.5B-exp.i1-IQ3_XXS.gguf
gguf · 432 MB · SHA-256 0245f47b7f1b…5a81 · Hugging Face
Baixar--- base_model: nanonets/Nanonets-OCR2-1.5B-exp language: - multilingual library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - OCR - image-to-text - pdf2markdown - VQA --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> <!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> weighted/imatrix quants of https://huggingface.co/nanonets/Nanonets-OCR2-1.5B-exp <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Nanonets-OCR2-1.5B-exp-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/Nanonets-OCR2-1.5B-exp-GGUF **This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Nanonets-OCR2-1.5B-exp-GGUF).** ## 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/Nanonets-OCR2-1.5B-exp-i1-GGUF/resolve/main/Nanonets-OCR2-1.5B-exp.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) | | [GGUF](https://huggingface.co/mradermacher/Nanonets-OCR2-1.5B-exp-i1-GGUF/resolve/main/Nanonets-OCR2-1.5B-exp.i1-IQ1_S.gguf) | i1-IQ1_S | 0.4 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/Nanonets-OCR2-1.5B-exp-i1-GGUF/resolve/main/Nanonets-OCR2-1.5B-exp.i1-IQ1_M.gguf) | i1-IQ1_M | 0.4 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/Nanonets-OCR2-1.5B-exp-i1-GGUF/resolve/main/Nanonets-OCR2-1.5B-exp.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.5 | | | [GGUF](https://huggingface.co/mradermacher/Nanonets-OCR2-1.5B-exp-i1-GGUF/resolve/main/Nanonets-OCR2-1.5B-exp.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.5 | | | [GGUF](https://huggingfa...
Source context: 838 downloads · 0 likes · Pipeline image-to-text · Library transformers · Repo mradermacher/Nanonets-OCR2-1.5B-exp-i1-GGUF
| i1-IQ2_XS |
| 0.5 |
| GGUF | i1-IQ2_S | 0.5 |
| GGUF | i1-IQ2_M | 0.5 |
| GGUF | i1-Q2_K_S | 0.6 | very low quality |
| GGUF | i1-IQ3_XXS | 0.6 | lower quality |
| GGUF | i1-Q2_K | 0.6 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XS | 0.6 |
| GGUF | i1-Q3_K_S | 0.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 0.6 | beats Q3_K* |
| GGUF | i1-IQ3_M | 0.6 |
| GGUF | i1-Q3_K_M | 0.7 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 0.7 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 0.7 |
| GGUF | i1-IQ4_NL | 0.7 | prefer IQ4_XS |
| GGUF | i1-Q4_0 | 0.7 | fast, low quality |
| GGUF | i1-Q4_K_S | 0.7 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 0.7 | fast, recommended |
| GGUF | i1-Q4_1 | 0.8 |
| GGUF | i1-Q5_K_S | 0.8 |
| GGUF | i1-Q5_K_M | 0.8 |
| GGUF | i1-Q6_K | 0.9 | practically like static Q6_K |
