Honkware/Qwopus3.6-27B-Fusion-BF16-exl3-6.0bpw

<div align="center">

Qwopus3.6 · 27B · Fusion · BF16

_{<code>EXL3</code> &nbsp;·&nbsp; <b>6.0&nbsp;bpw</b> &nbsp;·&nbsp; 23.3&nbsp;GB &nbsp;·&nbsp; Dense}

<br/>

   

  

</div>

[!NOTE] An ExLlamaV3 build of `KyleHessling1/Qwopus3.6-27B-Fusion-BF16` at 6.0 bits per weight. See Quants for sibling repos at other bit&#8209;widths or browse the collection.

Quants

<div align="center">

</div>

Inference

<table> <thead> <tr> <th align="left" width="32%">Loader</th> <th align="left">Use it for</th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/theroyallab/tabbyAPI"><b>TabbyAPI</b></a></td> <td>OpenAI&#8209;compatible HTTP server. Drop&#8209;in for OpenAI clients.</td> </tr> <tr> <td><a href="https://github.com/oobabooga/text-generation-webui"><b>text&#8209;generation&#8209;webui</b></a></td> <td>Local chat UI. Pick the <i>ExLlamaV3</i> loader from the model dropdown.</td> </tr> <tr> <td><a href="https://github.com/turboderp-org/exllamav3"><b>ExLlamaV3</b></a></td> <td>Direct Python API for embedding the model in your own code or pipeline.</td> </tr> </tbody> </table>

Download

pip install -U huggingface_hub

hf download \
  Honkware/Qwopus3.6-27B-Fusion-BF16-exl3-6.0bpw \
  --local-dir ./Qwopus3.6-27B-Fusion-BF16-exl3-6.0bpw

<details> <summary><b>Quantization recipe</b> &nbsp;_{(advanced, embedded in <code>quantization_config.json</code>)}</summary>

<br/>

Loaded automatically by every ExLlamaV3 loader; reproduced here for searchability.

</details>

License &amp; use

[!IMPORTANT] Use and license follow the [base model](https://huggingface.co/KyleHessling1/Qwopus3.6-27B-Fusion-BF16). Quantization adds no additional restrictions. Refer to the upstream repository for terms, citation, and safety documentation.

<div align="center"> _{<i>Quantized with <a href="https://github.com/Honkware/blockquant"><b>BlockQuant</b></a> &nbsp;·&nbsp; convention&nbsp;<code>{org}/{model}-exl3-{bpw}bpw</code></i>} </div>