Experimental News Clipping Site

Tag: memory requirements

  • Simon Willison’s Weblog: Gemma 3 QAT Models

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Apr/19/gemma-3-qat-models/ Source: Simon Willison’s Weblog Title: Gemma 3 QAT Models Feedly Summary: Gemma 3 QAT Models Interesting release from Google, as a follow-up to Gemma 3 from last month: To make Gemma 3 even more accessible, we are announcing new versions optimized with Quantization-Aware Training (QAT) that dramatically reduces memory requirements while maintaining…

  • Hacker News: How to Scale Your Model: A Systems View of LLMs on TPUs

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    Kurt Seifried
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    Source URL: https://jax-ml.github.io/scaling-book/ Source: Hacker News Title: How to Scale Your Model: A Systems View of LLMs on TPUs Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the performance optimization of large language models (LLMs) on tensor processing units (TPUs), addressing issues related to scaling and efficiency. It emphasizes the importance…

  • Hacker News: A step-by-step guide on deploying DeepSeek-R1 671B locally

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    Kurt Seifried
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    Source URL: https://snowkylin.github.io/blogs/a-note-on-deepseek-r1.html Source: Hacker News Title: A step-by-step guide on deploying DeepSeek-R1 671B locally Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text provides a detailed guide for deploying DeepSeek R1 671B AI models locally using ollama, including hardware requirements, installation steps, and observations on model performance. This information is particularly relevant…

  • Simon Willison’s Weblog: The impact of competition and DeepSeek on Nvidia

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Jan/27/deepseek-nvidia/ Source: Simon Willison’s Weblog Title: The impact of competition and DeepSeek on Nvidia Feedly Summary: The impact of competition and DeepSeek on Nvidia Long, excellent piece by Jeffrey Emanuel capturing the current state of the AI/LLM industry. The original title is “The Short Case for Nvidia Stock" – I’m using the Hacker…

  • Cloud Blog: How to deploy and serve multi-host gen AI large open models over GKE

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    system automation
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/deploy-and-serve-open-models-over-google-kubernetes-engine/ Source: Cloud Blog Title: How to deploy and serve multi-host gen AI large open models over GKE Feedly Summary: Context As generative AI experiences explosive growth fueled by advancements in LLMs (Large Language Models), access to open models is more critical than ever for developers. Open models are publicly available pre-trained foundational…

  • Hacker News: VPTQ: Extreme low-bit Quantization for real LLMs

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    Source URL: https://github.com/microsoft/VPTQ Source: Hacker News Title: VPTQ: Extreme low-bit Quantization for real LLMs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses a novel technique called Vector Post-Training Quantization (VPTQ) designed for compressing Large Language Models (LLMs) to extremely low bit-widths (under 2 bits) without compromising accuracy. This innovative method can…

  • Hacker News: NanoGPT (124M) quality in 3.25B training tokens (vs. 10B)

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    system automation
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    Source URL: https://github.com/KellerJordan/modded-nanogpt Source: Hacker News Title: NanoGPT (124M) quality in 3.25B training tokens (vs. 10B) Feedly Summary: Comments AI Summary and Description: Yes Summary: The provided text outlines a modified PyTorch trainer for GPT-2 that achieves training efficiency improvements through architectural updates and a novel optimizer. This is relevant for professionals in AI and…