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		<title><![CDATA[Inference - Community Announcements]]></title>
		<link>https://www.datasculpting.ai/inference/</link>
		<description><![CDATA[Inference - https://www.datasculpting.ai/inference]]></description>
		<pubDate>Mon, 26 Oct 2026 11:25:20 +0000</pubDate>
		<generator>MyBB</generator>
		<item>
			<title><![CDATA[Announcing VisLlama - a UI for engines]]></title>
			<link>https://www.datasculpting.ai/inference/showthread.php?tid=1501</link>
			<pubDate>Mon, 19 Oct 2026 05:25:13 +0000</pubDate>
			<dc:creator><![CDATA[<a href="https://www.datasculpting.ai/inference/member.php?action=profile&uid=2">Data Sculpting</a>]]></dc:creator>
			<guid isPermaLink="false">https://www.datasculpting.ai/inference/showthread.php?tid=1501</guid>
			<description><![CDATA[Hi all, sharing that I published a fairly robust UI wrapper for inference engines on Windows &amp; Linux, initial support is llama.cpp (including via Docker) and Strata - adding new engines should be as simple as a JSON definition (next phase is engine expansion) - the UI already supports just about everything needed.<br />
<br />
<a href="https://github.com/DataSculpting/VisLlama" target="_blank" rel="noopener" class="mycode_url">https://github.com/DataSculpting/VisLlama</a> <br />
<br />
It's not just a UI, it allows juggling of multiple engine build presets, multiple model presets, allows everything manageable via UI, GPU assignment including priority and typical splits, auto-launch, launch order. It's everything LM Studio or Ollama should be but aren't. It also puts ALL loaded models (regardless of engine) behind a common OpenAI-compatible endpoint and has separate router management options. Built-in chat, system stats, historical inference stats, etc.]]></description>
			<content:encoded><![CDATA[Hi all, sharing that I published a fairly robust UI wrapper for inference engines on Windows &amp; Linux, initial support is llama.cpp (including via Docker) and Strata - adding new engines should be as simple as a JSON definition (next phase is engine expansion) - the UI already supports just about everything needed.<br />
<br />
<a href="https://github.com/DataSculpting/VisLlama" target="_blank" rel="noopener" class="mycode_url">https://github.com/DataSculpting/VisLlama</a> <br />
<br />
It's not just a UI, it allows juggling of multiple engine build presets, multiple model presets, allows everything manageable via UI, GPU assignment including priority and typical splits, auto-launch, launch order. It's everything LM Studio or Ollama should be but aren't. It also puts ALL loaded models (regardless of engine) behind a common OpenAI-compatible endpoint and has separate router management options. Built-in chat, system stats, historical inference stats, etc.]]></content:encoded>
		</item>
		<item>
			<title><![CDATA[Small rules clarification: early impressions]]></title>
			<link>https://www.datasculpting.ai/inference/showthread.php?tid=1015</link>
			<pubDate>Sat, 10 Oct 2026 20:19:02 +0000</pubDate>
			<dc:creator><![CDATA[<a href="https://www.datasculpting.ai/inference/member.php?action=profile&uid=84">oxiderunner</a>]]></dc:creator>
			<guid isPermaLink="false">https://www.datasculpting.ai/inference/showthread.php?tid=1015</guid>
			<description><![CDATA[Spent some time on this today and wanted to compare notes.<br />
<br />
Two paths both seem viable, but they break down differently once workstation thermals becomes important.<br />
<br />
Interested in tradeoffs more than fan loyalty.<br />
<br />
This is mostly for local work rather than public serving.<br />
<br />
The part that surprised me was how much the boring details mattered more than the model choice.]]></description>
			<content:encoded><![CDATA[Spent some time on this today and wanted to compare notes.<br />
<br />
Two paths both seem viable, but they break down differently once workstation thermals becomes important.<br />
<br />
Interested in tradeoffs more than fan loyalty.<br />
<br />
This is mostly for local work rather than public serving.<br />
<br />
The part that surprised me was how much the boring details mattered more than the model choice.]]></content:encoded>
		</item>
		<item>
			<title><![CDATA[Forum structure feedback thread on 4090]]></title>
			<link>https://www.datasculpting.ai/inference/showthread.php?tid=344</link>
			<pubDate>Sat, 19 Sep 2026 00:02:43 +0000</pubDate>
			<dc:creator><![CDATA[<a href="https://www.datasculpting.ai/inference/member.php?action=profile&uid=79">sparrowworks88</a>]]></dc:creator>
			<guid isPermaLink="false">https://www.datasculpting.ai/inference/showthread.php?tid=344</guid>
			<description><![CDATA[Thought I'd post a small recipe because a lot of threads ask similar things.<br />
<br />
This isn't revolutionary, but the combination of LM Studio and M3 Max felt surprisingly usable once I tuned around continuous batching.<br />
<br />
If someone wants the exact settings I can clean them up and post them.]]></description>
			<content:encoded><![CDATA[Thought I'd post a small recipe because a lot of threads ask similar things.<br />
<br />
This isn't revolutionary, but the combination of LM Studio and M3 Max felt surprisingly usable once I tuned around continuous batching.<br />
<br />
If someone wants the exact settings I can clean them up and post them.]]></content:encoded>
		</item>
		<item>
			<title><![CDATA[Small rules clarification for DeepSeek]]></title>
			<link>https://www.datasculpting.ai/inference/showthread.php?tid=248</link>
			<pubDate>Sun, 13 Sep 2026 05:03:51 +0000</pubDate>
			<dc:creator><![CDATA[<a href="https://www.datasculpting.ai/inference/member.php?action=profile&uid=53">batchember</a>]]></dc:creator>
			<guid isPermaLink="false">https://www.datasculpting.ai/inference/showthread.php?tid=248</guid>
			<description><![CDATA[Maybe I'm missing something obvious.<br />
<br />
My current setup is SGLang with 5090, and I keep running into reranking.<br />
<br />
Not looking for the perfect answer, mostly what worked in real use.]]></description>
			<content:encoded><![CDATA[Maybe I'm missing something obvious.<br />
<br />
My current setup is SGLang with 5090, and I keep running into reranking.<br />
<br />
Not looking for the perfect answer, mostly what worked in real use.]]></content:encoded>
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