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For a convenient overview and download list, visit our model page for this model.
Modellquelle
Quellenbeschreibung
weighted/imatrix quants of https://huggingface.co/prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it
For a convenient overview and download list, visit our model page for this model.
static quants are available at
Quellen
1 QuelleVerifiziert 17. Sept.
Modellartefakte
25 ArtefakteQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ1_M.gguf
gguf · 1,90 GB · SHA-256 b061f911f8dd…a098 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ1_S.gguf
gguf · 1,77 GB · SHA-256 cc7bc994b121…82c2 · Hugging Face
HerunterladenQuellenauszüge
2 AuszügeThis 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 | 2.0 | for the desperate |
| GGUF | i1-IQ1_M | 2.1 | mostly desperate |
| GGUF | i1-IQ2_XXS | 2.4 |
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.
Qwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ2_M.gguf
gguf · 2,59 GB · SHA-256 c8b814695001…c2e0 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ2_S.gguf
gguf · 2,42 GB · SHA-256 24cfa59ae810…49db · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ2_XS.gguf
gguf · 2,30 GB · SHA-256 cd2a68b59c94…840a · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ2_XXS.gguf
gguf · 2,12 GB · SHA-256 961d80d52b4b…529c · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ3_M.gguf
gguf · 3,33 GB · SHA-256 162b8bde9149…b9f6 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ3_S.gguf
gguf · 3,26 GB · SHA-256 7020374dff14…e339 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ3_XS.gguf
gguf · 3,12 GB · SHA-256 32bdd05a421d…6660 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ3_XXS.gguf
gguf · 2,90 GB · SHA-256 b0121602fc7e…a47f · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ4_NL.gguf
gguf · 4,13 GB · SHA-256 c621e5bd0e86…f102 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ4_XS.gguf
gguf · 3,93 GB · SHA-256 28c916be62e6…c231 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q2_K_S.gguf
gguf · 2,64 GB · SHA-256 7141fca12519…e6cd · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q2_K.gguf
gguf · 2,81 GB · SHA-256 bc1152811f01…94ab · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q3_K_L.gguf
gguf · 3,81 GB · SHA-256 ef0bcdfc6faf…4952 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q3_K_M.gguf
gguf · 3,55 GB · SHA-256 1baa01090cf1…af80 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q3_K_S.gguf
gguf · 3,25 GB · SHA-256 f7417f9f986e…2a21 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q4_0.gguf
gguf · 4,14 GB · SHA-256 e7b793fe1452…1c04 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q4_1.gguf
gguf · 4,54 GB · SHA-256 ad3c14f8f09d…df73 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q4_K_M.gguf
gguf · 4,36 GB · SHA-256 3b823955e838…58c2 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q4_K_S.gguf
gguf · 4,15 GB · SHA-256 6efe3e21ea56…ad93 · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q5_K_M.gguf
gguf · 5,07 GB · SHA-256 9b05b9f08f39…e37e · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q5_K_S.gguf
gguf · 4,95 GB · SHA-256 25b49445d25a…760a · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.i1-Q6_K.gguf
gguf · 5,82 GB · SHA-256 95d8e55df55c…3cba · Hugging Face
HerunterladenQwen2.5-VL-7B-Abliterated-Caption-it.imatrix.gguf
gguf · 4,35 MB · SHA-256 69642d2a9c4a…ed08 · Hugging Face
Herunterladen--- base_model: prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it datasets: - prithivMLmods/blip3o-caption-mini-arrow - prithivMLmods/Caption3o-Opt-v2 language: - en - zh - th library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - text-generation-inference - uncensored - image-captioning - vlm - visual-understanding - caption - image-to-text --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> weighted/imatrix quants of https://huggingface.co/prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-GGUF **This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-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/Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF/resolve/main/Qwen2.5-VL-7B-Abliterated-Caption-it.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF/resolve/main/Qwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF/resolve/main/Qwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF/resolve/main/Qwen2.5-VL-7B-Abliterated-Caption-it.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abl...
Source context: 2335 downloads · 8 likes · Pipeline image-to-text · Library transformers · Repo mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF
| GGUF | i1-IQ2_XS | 2.6 |
| GGUF | i1-IQ2_S | 2.7 |
| GGUF | i1-IQ2_M | 2.9 |
| GGUF | i1-Q2_K_S | 2.9 | very low quality |
| GGUF | i1-Q2_K | 3.1 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 3.2 | lower quality |
| GGUF | i1-IQ3_XS | 3.4 |
| GGUF | i1-Q3_K_S | 3.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 3.6 | beats Q3_K* |
| GGUF | i1-IQ3_M | 3.7 |
| GGUF | i1-Q3_K_M | 3.9 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 4.2 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 4.3 |
| GGUF | i1-IQ4_NL | 4.5 | prefer IQ4_XS |
| GGUF | i1-Q4_0 | 4.5 | fast, low quality |
| GGUF | i1-Q4_K_S | 4.6 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 4.8 | fast, recommended |
| GGUF | i1-Q4_1 | 5.0 |
| GGUF | i1-Q5_K_S | 5.4 |
| GGUF | i1-Q5_K_M | 5.5 |
| GGUF | i1-Q6_K | 6.4 | practically like static Q6_K |
