May 2025 - Blablador-news - lists.fz-juelich.de

Hi
by Na, Sehyang 27 May '25

27 May '25

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Helmholtz services downtime on 2025-05-22 16:00 CEST, for approx. 1 hour.
by Strube, Alexandre 20 May '25

20 May '25

This is coming from the HIFIS team: > Dear Helmholtz Cloud users: > Helmholtz Codebase [1] and Mattermost [2] will undergo planned maintenance and will not be accessible from 2025-05-22 16:00 CEST, for approx. 1 hour. > In preparation for the GitLab major upgrade 18, a planned maintenance of the database is taking place. Access to both services is not possible during this time. > With regards, > the HIFIS team In practice: Blablador’s API server won’t be able to authenticate the token, so it will fail. I’m sorry for the disturbance. Best, Alex

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Llama3-405 is out for tomorrow
by Strube, Alexandre 14 May '25

14 May '25

Hello Blabladores, as the West AI machine that we run Llama3-405 on is on testing tomorrow, you probably noticed that the model is out, and it will be for the whole day tomorrow. Sorry for the inconvenience. Alex

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Attempting to phase out llama3.3 for alias-large in favor of Qwen3-30B-A3B
by Strube, Alexandre 05 May '25

05 May '25

Hello Blabladores! In keeping with the latest developments in LLMs, I decided to try Qwen-3 30B - A3B. This is a much smaller model than Llama 3.3 - 70B, as well as as the previous model running as alias-large, DeepSeek-R1-70B, which was not so good and very unstable. This is a Mixture of Experts (MoE) model, with 30 billion parameters, where each expert has 3 billion parameters. This means a number of things: - Given the model is much smaller, we can have a much bigger context size, as there is more GPU memory available. The consquence is that the model is more useful with bigger workloads and agents. While I had to keep Llama 3.3-70 limited to a maximum context size of 8192 tokens, I can let Qwen-3 run at its maximum size, which is 128k tokens. - The mixture of experts model architecture means that, when activated, you are performing inference only on one expert at a time, and this is of 3 billion parameters - meaning it is MUCH faster, which makes it again more useful. Qwen3 is a much more modern model than the Llama3.3 - Five months in this field can make a huge difference. Besides, Qwen3 uses the Apache-2.0 license, and I am much more partial to it than to the arcane Meta Llama License which should not even exist. Mind you that while this is a reasoning model, I had to remove the reasoning part on the chat template - This is because the thinking process was causing the web ui to fail intermittently. When I get a fix on that, I will remove the setting so you can see the reasoning process. This affects both the Web UI and the API access. The chat template have a sep="<|im_end|>/nothink", so the model never reasons. If you have any feedback on the workings of the model, or if you think the quality has suffered, please let me know right away! In the worst case I would revert to Llama3.3. But I hope it won’t be needed! Let’s bark! Alex

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