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TreeVGR 7B CI GGUF

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

Sourcehuggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/tree/72c1d607629beb0369e1a828dfe6098502991e9f
KindOtherBase modelHaochenWang/TreeVGR-7B-CIVersionRevision 72c1d60Bgrade

Model source

Kind
Other
File size
814 MB–14.2 GB
Base model
HaochenWang/TreeVGR-7B-CI
Version
vRevision 72c1d60
Updated
Oct 23, 2026
Downloads
261
Source
Hugging Face

Source description

About

static quants of https://huggingface.co/HaochenWang/TreeVGR-7B-CI

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/TreeVGR-7B-CI-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_01.0multi-modal supplement
GGUFmmproj-f161.5multi-modal supplement
GGUFQ2_K3.1
GGUFQ3_K_S3.6
GGUFQ3_K_M3.9lower quality
GGUFQ3_K_L4.2
GGUFIQ4_XS4.4
GGUFQ4_K_S4.6fast, recommended
GGUFQ4_K_M4.8fast, recommended
GGUFQ5_K_S5.4
GGUFQ5_K_M5.5
GGUFQ6_K6.4very good quality
GGUFQ8_08.2fast, best quality
GGUFf1615.316 bpw, overkill

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 FacePrimaryVersion 72c1d607629beb0369e1a828dfe6098502991e9f
huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/tree/72c1d607629beb0369e1a828dfe6098502991e9f

Verified Oct 23

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Model artifacts

14 artifacts

TreeVGR-7B-CI.f16.gguf

gguf · 14.2 GB · SHA-256 525b92597f52…1373 · Hugging Face

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TreeVGR-7B-CI.IQ4_XS.gguf

gguf · 3.96 GB · SHA-256 b52dfcb2161f…0967 · Hugging Face

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TreeVGR-7B-CI.mmproj-f16.gguf

gguf · 1.26 GB · SHA-256 625b635436e1…4d32 · Hugging Face

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TreeVGR-7B-CI.mmproj-Q8_0.gguf

gguf · 814 MB · SHA-256 6a7be9f03eb4…bd30 · Hugging Face

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TreeVGR-7B-CI.Q2_K.gguf

gguf · 2.81 GB · SHA-256 c5dac2906ef9…a7fe · Hugging Face

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TreeVGR-7B-CI.Q3_K_L.gguf

gguf · 3.81 GB · SHA-256 93e3250e85ba…70e8 · Hugging Face

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TreeVGR-7B-CI.Q3_K_M.gguf

gguf · 3.55 GB · SHA-256 fd29a9584adc…4787 · Hugging Face

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TreeVGR-7B-CI.Q3_K_S.gguf

gguf · 3.25 GB · SHA-256 ff4e3d262579…cd46 · Hugging Face

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TreeVGR-7B-CI.Q4_K_M.gguf

gguf · 4.36 GB · SHA-256 4d0ecf849072…a15f · Hugging Face

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TreeVGR-7B-CI.Q4_K_S.gguf

gguf · 4.15 GB · SHA-256 644ce68ec2be…29a1 · Hugging Face

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TreeVGR-7B-CI.Q5_K_M.gguf

gguf · 5.07 GB · SHA-256 f60f1edfa047…c715 · Hugging Face

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TreeVGR-7B-CI.Q5_K_S.gguf

gguf · 4.95 GB · SHA-256 37f4a02d6cfa…71b1 · Hugging Face

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TreeVGR-7B-CI.Q6_K.gguf

gguf · 5.82 GB · SHA-256 2428d1f7d36e…56dc · Hugging Face

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TreeVGR-7B-CI.Q8_0.gguf

gguf · 7.54 GB · SHA-256 a1e96e9bcf89…d72e · Hugging Face

Download file

Source excerpts

3 excerpts
ReadmeAug 6huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF

--- base_model: HaochenWang/TreeVGR-7B-CI datasets: - HaochenWang/TreeBench - HaochenWang/TreeVGR-RL-37K - HaochenWang/TreeVGR-SFT-35K language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - visual-question-answering - visual-grounding - visual-reasoning - qwen --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> static quants of https://huggingface.co/HaochenWang/TreeVGR-7B-CI <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#TreeVGR-7B-CI-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/TreeVGR-7B-CI-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/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 1.0 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.mmproj-f16.gguf) | mmproj-f16 | 1.5 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.Q2_K.gguf) | Q2_K | 3.1 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.Q3_K_S.gguf) | Q3_K_S | 3.6 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.Q3_K_L.gguf) | Q3_K_L | 4.2 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.IQ4_XS.gguf) | IQ4_XS | 4.4 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B-CI.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF/resolve/main/TreeVGR-7B...

NoteOct 23huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF

Source context: 261 downloads · 1 likes · Pipeline visual-question-answering · Library transformers · Repo mradermacher/TreeVGR-7B-CI-GGUF

NoteAug 6huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF

Source context: 103 downloads · 1 likes · Pipeline visual-question-answering · Library transformers · Repo mradermacher/TreeVGR-7B-CI-GGUF