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Model: mradermacher/QwenGuard-v1.2-7B-GGUF Source: Original Platform
2026-05-26 02:46:16 +08:00
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+---
+base_model: AIML-TUDA/QwenGuard-v1.2-7B
+datasets: AIML-TUDA/LlavaGuard
+extra_gated_fields:
+  Affiliation: text
+  Country: text
+  Email: text
+  ? I have explicitly checked that downloading LlavaGuard is legal in my jurisdiction,
+    in the country/region where I am located right now, and for the use case that
+    I have described above, I have also read and accepted the relevant Terms of Use
+  : checkbox
+  Name: text
+extra_gated_prompt: By filling out the form below I understand that LlavaGuard is
+  a derivative model based on webscraped images and the SMID dataset that use individual
+  licenses and their respective terms and conditions apply. I understand that all
+  content uses are subject to the terms of use. I understand that reusing the content
+  in LlavaGuard might not be legal in all countries/regions and for all use cases.
+  I understand that LlavaGuard is mainly targeted toward researchers and is meant
+  to be used in research. LlavaGuard authors reserve the right to revoke my access
+  to this data. They reserve the right to modify this data at any time in accordance
+  with take-down requests.
+language:
+- en
+library_name: transformers
+mradermacher:
+  readme_rev: 1
+quantized_by: mradermacher
+tags:
+- llama-factory
+- freeze
+- generated_from_trainer
+---
+## About
+
+<!-- ### quantize_version: 2 -->
+<!-- ### output_tensor_quantised: 1 -->
+<!-- ### convert_type: hf -->
+<!-- ### vocab_type:  -->
+<!-- ### tags:  -->
+static quants of https://huggingface.co/AIML-TUDA/QwenGuard-v1.2-7B
+
+<!-- provided-files -->
+
+***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#QwenGuard-v1.2-7B-GGUF).***
+
+weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
+## 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/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 1.0 | multi-modal supplement |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.mmproj-f16.gguf) | mmproj-f16 | 1.5 | multi-modal supplement |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q2_K.gguf) | Q2_K | 3.1 |  |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q3_K_S.gguf) | Q3_K_S | 3.6 |  |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q3_K_L.gguf) | Q3_K_L | 4.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.IQ4_XS.gguf) | IQ4_XS | 4.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q5_K_S.gguf) | Q5_K_S | 5.4 |  |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q5_K_M.gguf) | Q5_K_M | 5.5 |  |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
+| [GGUF](https://huggingface.co/mradermacher/QwenGuard-v1.2-7B-GGUF/resolve/main/QwenGuard-v1.2-7B.f16.gguf) | f16 | 15.3 | 16 bpw, overkill |
+
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.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](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time.
+
+<!-- end -->