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Gemma4 31B Finetuned V2 GGUF

For a convenient overview and download list, visit our model page for this model.

TypeOtherModèle de baseSF-Foundation/Gemma4-31B-Finetuned-V2VersionRevision 78dced1Éditeur@mradermacherCClasse

Source du modèle

Type
Other
Taille du fichier
772 MB–30,4 GB
Modèle de base
SF-Foundation/Gemma4-31B-Finetuned-V2
Version
vRevision 78dced1
Mis à jour
4 oct. 2026
Téléchargements
727
Paramètres
31B
Source
Hugging Face

Description de la source

About

static quants of https://huggingface.co/SF-Foundation/Gemma4-31B-Finetuned-V2

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-i1-GGUF

Usage

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.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

LinkTypeSize/GBNotes
GGUFmmproj-Q8_00.9multi-modal supplement
GGUFmmproj-f161.3multi-modal supplement
GGUFQ2_K12.0
GGUFQ3_K_S13.9
GGUFQ3_K_M15.4lower quality
GGUFQ3_K_L16.7
GGUFIQ4_XS17.0
GGUFQ4_K_S17.9fast, recommended
GGUFQ4_K_M18.8fast, recommended
GGUFQ5_K_S21.4
GGUFQ5_K_M21.9
GGUFQ6_K25.3very good quality
GGUFQ8_032.7fast, best quality

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

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

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.

Sources

1 source
Hugging FacePrincipalVersion 78dced134d5e4d3e5df7855d7d2021a1b5f24c0b
huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/tree/78dced134d5e4d3e5df7855d7d2021a1b5f24c0b

Vérifié 4 oct.

Artefacts du modèle

13 artefacts

Gemma4-31B-Finetuned-V2.IQ4_XS.gguf

gguf · 15,7 GB · SHA-256 1df60d63a491…34b7 · Hugging Face

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Gemma4-31B-Finetuned-V2.mmproj-f16.gguf

gguf · 1,12 GB · SHA-256 d8dc4e16f7aa…ca0f · Hugging Face

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Gemma4-31B-Finetuned-V2.mmproj-Q8_0.gguf

gguf · 772 MB · SHA-256 70c19a006b38…b8fb · Hugging Face

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Gemma4-31B-Finetuned-V2.Q2_K.gguf

gguf · 11,1 GB · SHA-256 8de184159866…8835 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q3_K_L.gguf

gguf · 15,5 GB · SHA-256 ec95d0a324d6…e4db · Hugging Face

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Gemma4-31B-Finetuned-V2.Q3_K_M.gguf

gguf · 14,2 GB · SHA-256 884a749dd339…6802 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q3_K_S.gguf

gguf · 12,8 GB · SHA-256 f007d65f87ed…50a5 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q4_K_M.gguf

gguf · 17,4 GB · SHA-256 b8e4f679cc2e…09e4 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q4_K_S.gguf

gguf · 16,5 GB · SHA-256 4476b0dc38d5…ceb1 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q5_K_M.gguf

gguf · 20,3 GB · SHA-256 c8cfeea8d52a…8d87 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q5_K_S.gguf

gguf · 19,8 GB · SHA-256 627924117fc2…ff4b · Hugging Face

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Gemma4-31B-Finetuned-V2.Q6_K.gguf

gguf · 23,5 GB · SHA-256 eb78d03b1eb8…2e38 · Hugging Face

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Gemma4-31B-Finetuned-V2.Q8_0.gguf

gguf · 30,4 GB · SHA-256 917699057581…d6ab · Hugging Face

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Extraits de sources

3 extraits

--- base_model: SF-Foundation/Gemma4-31B-Finetuned-V2 language: - en library_name: transformers mradermacher: readme_rev: 1 quantized_by: mradermacher --- ## 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/SF-Foundation/Gemma4-31B-Finetuned-V2 <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Gemma4-31B-Finetuned-V2-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-i1-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/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.9 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.mmproj-f16.gguf) | mmproj-f16 | 1.3 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.Q2_K.gguf) | Q2_K | 12.0 | | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.Q3_K_S.gguf) | Q3_K_S | 13.9 | | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.Q3_K_M.gguf) | Q3_K_M | 15.4 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.Q3_K_L.gguf) | Q3_K_L | 16.7 | | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve/main/Gemma4-31B-Finetuned-V2.IQ4_XS.gguf) | IQ4_XS | 17.0 | | | [GGUF](https://huggingface.co/mradermacher/Gemma4-31B-Finetuned-V2-GGUF/resolve...

Source context: 727 downloads · 1 likes · Library transformers · Repo mradermacher/Gemma4-31B-Finetuned-V2-GGUF

Source context: 1032 downloads · 0 likes · Library transformers · Repo mradermacher/Gemma4-31B-Finetuned-V2-GGUF