Experimental News Clipping Site

Tag: Huggingface

  • Simon Willison’s Weblog: Qwen3-8B

    —

    by

    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/May/2/qwen3-8b/#atom-everything Source: Simon Willison’s Weblog Title: Qwen3-8B Feedly Summary: Having tried a few of the Qwen 3 models now my favorite is a bit of a surprise to me: I’m really enjoying Qwen3-8B. I’ve been running prompts through the MLX 4bit quantized version, mlx-community/Qwen3-8B-4bit. I’m using llm-mlx like this: llm install llm-mlx llm…

  • Docker: Introducing Docker Model Runner: A Better Way to Build and Run GenAI Models Locally

    —

    by

    Kurt Seifried
    in

    Source URL: https://www.docker.com/blog/introducing-docker-model-runner/ Source: Docker Title: Introducing Docker Model Runner: A Better Way to Build and Run GenAI Models Locally Feedly Summary: Docker Model Runner is a faster, simpler way to run and test AI models locally, right from your existing workflow. AI Summary and Description: Yes Summary: The text discusses the launch of Docker…

  • Hacker News: Sharding Pgvector

    —

    by

    Kurt Seifried
    in

    Source URL: https://pgdog.dev/blog/sharding-pgvector Source: Hacker News Title: Sharding Pgvector Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the implementation of a sharding strategy for handling vector indices in the pgvector database, focusing specifically on large-scale embeddings. It highlights the challenges of scaling vector searches and presents an approach using two indexing…

  • Hacker News: Sharding Pgvector

    —

    by

    Kurt Seifried
    in

    Source URL: https://pgdog.dev/blog/sharding-pgvector Source: Hacker News Title: Sharding Pgvector Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses the implementation of a sharding strategy for handling vector indices in the pgvector database, focusing specifically on large-scale embeddings. It highlights the challenges of scaling vector searches and presents an approach using two indexing…

  • Simon Willison’s Weblog: mlx-community/OLMo-2-0325-32B-Instruct-4bit

    —

    by

    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Mar/16/olmo2/#atom-everything Source: Simon Willison’s Weblog Title: mlx-community/OLMo-2-0325-32B-Instruct-4bit Feedly Summary: mlx-community/OLMo-2-0325-32B-Instruct-4bit OLMo 2 32B claims to be “the first fully-open model (all data, code, weights, and details are freely available) to outperform GPT3.5-Turbo and GPT-4o mini". Thanks to the MLX project here’s a recipe that worked for me to run it on my Mac,…

  • Hacker News: Simple Explanation of LLMs

    —

    by

    Kurt Seifried
    in

    Source URL: https://blog.oedemis.io/understanding-llms-a-simple-guide-to-large-language-models Source: Hacker News Title: Simple Explanation of LLMs Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text provides a comprehensive overview of Large Language Models (LLMs), highlighting their rapid adoption in AI, the foundational concepts behind their architecture, such as attention mechanisms and tokenization, and their implications for various fields.…

  • Simon Willison’s Weblog: LLM 0.22, the annotated release notes

    —

    by

    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Feb/17/llm/#atom-everything Source: Simon Willison’s Weblog Title: LLM 0.22, the annotated release notes Feedly Summary: I released LLM 0.22 this evening. Here are the annotated release notes: model.prompt(…, key=) for API keys chatgpt-4o-latest llm logs -s/–short llm models -q gemini -q exp llm embed-multi –prepend X Everything else model.prompt(…, key=) for API keys Plugins…

  • Simon Willison’s Weblog: Run LLMs on macOS using llm-mlx and Apple’s MLX framework

    —

    by

    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Feb/15/llm-mlx/#atom-everything Source: Simon Willison’s Weblog Title: Run LLMs on macOS using llm-mlx and Apple’s MLX framework Feedly Summary: llm-mlx is a brand new plugin for my LLM Python Library and CLI utility which builds on top of Apple’s excellent MLX array framework library and mlx-lm package. If you’re a terminal user or Python…