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Tag: Qwen

  • Simon Willison’s Weblog: Defeating Nondeterminism in LLM Inference

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Sep/11/defeating-nondeterminism/#atom-everything Source: Simon Willison’s Weblog Title: Defeating Nondeterminism in LLM Inference Feedly Summary: Defeating Nondeterminism in LLM Inference A very common question I see about LLMs concerns why they can’t be made to deliver the same response to the same prompt by setting a fixed random number seed. Like many others I had…

  • The Register: Tinker with LLMs in the privacy of your own home using Llama.cpp

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    Kurt Seifried
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    Source URL: https://www.theregister.com/2025/08/24/llama_cpp_hands_on/ Source: The Register Title: Tinker with LLMs in the privacy of your own home using Llama.cpp Feedly Summary: Everything you need to know to build, run, serve, optimize and quantize models on your PC Hands on Training large language models (LLMs) may require millions or even billion of dollars of infrastructure, but…

  • Slashdot: China’s Lead in Open-Source AI Jolts Washington and Silicon Valley

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    Kurt Seifried
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    Source URL: https://news.slashdot.org/story/25/08/13/1536215/chinas-lead-in-open-source-ai-jolts-washington-and-silicon-valley?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: China’s Lead in Open-Source AI Jolts Washington and Silicon Valley Feedly Summary: AI Summary and Description: Yes Summary: The text highlights China’s advancements in open-source AI, particularly how their leading model surpasses that of OpenAI, raising significant concerns among U.S. policymakers and the tech industry. This shift emphasizes the…

  • Simon Willison’s Weblog: Qwen3-4B-Thinking: "This is art – pelicans don’t ride bikes!"

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/10/qwen3-4b/#atom-everything Source: Simon Willison’s Weblog Title: Qwen3-4B-Thinking: "This is art – pelicans don’t ride bikes!" Feedly Summary: I’ve fallen a few days behind keeping up with Qwen. They released two new 4B models last week: Qwen3-4B-Instruct-2507 and its thinking equivalent Qwen3-4B-Thinking-2507. These are relatively tiny models that punch way above their weight. I’ve…

  • Simon Willison’s Weblog: Qwen3-4B Instruct and Thinking

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/6/qwen3-4b-instruct-and-thinking/ Source: Simon Willison’s Weblog Title: Qwen3-4B Instruct and Thinking Feedly Summary: Qwen3-4B Instruct and Thinking Yet another interesting model from Qwen—these are tiny compared to their other recent releases (just 4B parameters, 7.5GB on Hugging Face and even smaller when quantized) but with a 262,144 context length, which Qwen suggest is essential…

  • Simon Willison’s Weblog: OpenAI’s new open weight (Apache 2) models are really good

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/5/gpt-oss/ Source: Simon Willison’s Weblog Title: OpenAI’s new open weight (Apache 2) models are really good Feedly Summary: The long promised OpenAI open weight models are here, and they are very impressive. They’re available under proper open source licenses – Apache 2.0 – and come in two sizes, 120B and 20B. OpenAI’s own…

  • Cloud Blog: Announcements for AI Hypercomputer: The latest infrastructure news for ML practitioners

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/q2-2025-ai-hypercomputer-updates/ Source: Cloud Blog Title: Announcements for AI Hypercomputer: The latest infrastructure news for ML practitioners Feedly Summary: Curious about the latest in AI infrastructure from Google Cloud? Every three months we share a roundup of the latest AI Hypercomputer news, resources, events, learning opportunities, and more. Read on to learn new ways…