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For a convenient overview and download list, visit our model page for this model.
Modellquelle
Quellenbeschreibung
static quants of https://huggingface.co/huihui-ai/Qwen2.5-VL-7B-Instruct-abliterated
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at
Quellen
1 QuelleVerifiziert 14. Okt.
Modellartefakte
14 ArtefakteQwen2.5-VL-7B-Instruct-abliterated.f16.gguf
gguf · 14,2 GB · SHA-256 cf32c5fd917f…ffaf · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.IQ4_XS.gguf
gguf · 3,96 GB · SHA-256 8bd90ee4b6ef…b6c5 · Hugging Face
HerunterladenQuellenauszüge
2 AuszügeIf 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 | mmproj-Q8_0 | 1.0 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.5 | multi-modal supplement |
| GGUF | Q2_K | 3.1 | |
| GGUF | Q3_K_S | 3.6 |
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.
Qwen2.5-VL-7B-Instruct-abliterated.mmproj-f16.gguf
gguf · 1,26 GB · SHA-256 7e109bb57651…23e8 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.mmproj-Q8_0.gguf
gguf · 814 MB · SHA-256 fa7c77569880…d1af · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q2_K.gguf
gguf · 2,81 GB · SHA-256 843c391214eb…af2a · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q3_K_L.gguf
gguf · 3,81 GB · SHA-256 9c40606956c1…d824 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q3_K_M.gguf
gguf · 3,55 GB · SHA-256 ce75380629ad…d4c2 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q3_K_S.gguf
gguf · 3,25 GB · SHA-256 dab02f52f8d6…d531 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q4_K_M.gguf
gguf · 4,36 GB · SHA-256 adc8b3a04786…21c9 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q4_K_S.gguf
gguf · 4,15 GB · SHA-256 c656bd9874d3…290e · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q5_K_M.gguf
gguf · 5,07 GB · SHA-256 e9957d8091af…6cb7 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q5_K_S.gguf
gguf · 4,95 GB · SHA-256 1c51c93a0474…30fb · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q6_K.gguf
gguf · 5,82 GB · SHA-256 6e96f5164e64…f8b2 · Hugging Face
HerunterladenQwen2.5-VL-7B-Instruct-abliterated.Q8_0.gguf
gguf · 7,54 GB · SHA-256 669a5604c47c…e7d0 · Hugging Face
Herunterladen--- base_model: huihui-ai/Qwen2.5-VL-7B-Instruct-abliterated 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: --> static quants of https://huggingface.co/huihui-ai/Qwen2.5-VL-7B-Instruct-abliterated <!-- 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-Instruct-abliterated-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-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/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 1.0 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.mmproj-f16.gguf) | mmproj-f16 | 1.5 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.Q2_K.gguf) | Q2_K | 3.1 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.Q3_K_S.gguf) | Q3_K_S | 3.6 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.Q3_K_L.gguf) | Q3_K_L | 4.2 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.IQ4_XS.gguf) | IQ4_XS | 4.4 | | | [GGUF](https://huggingface.co/mradermacher/Q...
Source context: 45698 downloads · 56 likes · Library transformers · Repo mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF
| GGUF | Q3_K_M | 3.9 | lower quality |
| GGUF | Q3_K_L | 4.2 |
| GGUF | IQ4_XS | 4.4 |
| GGUF | Q4_K_S | 4.6 | fast, recommended |
| GGUF | Q4_K_M | 4.8 | fast, recommended |
| GGUF | Q5_K_S | 5.4 |
| GGUF | Q5_K_M | 5.5 |
| GGUF | Q6_K | 6.4 | very good quality |
| GGUF | Q8_0 | 8.2 | fast, best quality |
| GGUF | f16 | 15.3 | 16 bpw, overkill |
