Experimental News Clipping Site

Tag: llama

  • Hacker News: Full LLM training and evaluation toolkit

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    Source URL: https://github.com/huggingface/smollm Source: Hacker News Title: Full LLM training and evaluation toolkit Feedly Summary: Comments AI Summary and Description: Yes Summary: The text introduces SmolLM2, a family of compact language models with varying parameters designed for lightweight, on-device applications, and details on how they can be utilized in different scenarios. Such advancements in AI…

  • Simon Willison’s Weblog: Quantization matters

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    Source URL: https://simonwillison.net/2024/Nov/23/quantization-matters/#atom-everything Source: Simon Willison’s Weblog Title: Quantization matters Feedly Summary: Quantization matters What impact does quantization have on the performance of an LLM? been wondering about this for quite a while, now here are numbers from Paul Gauthier. He ran differently quantized versions of Qwen 2.5 32B Instruct through his Aider code editing…

  • Hacker News: Show HN: Llama 3.2 Interpretability with Sparse Autoencoders

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    Source URL: https://github.com/PaulPauls/llama3_interpretability_sae Source: Hacker News Title: Show HN: Llama 3.2 Interpretability with Sparse Autoencoders Feedly Summary: Comments AI Summary and Description: Yes Summary: The provided text outlines a research project focused on the interpretability of the Llama 3 language model using Sparse Autoencoders (SAEs). This project aims to extract more clearly interpretable features from…

  • Simon Willison’s Weblog: llm-gguf 0.2, now with embeddings

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    Source URL: https://simonwillison.net/2024/Nov/21/llm-gguf-embeddings/#atom-everything Source: Simon Willison’s Weblog Title: llm-gguf 0.2, now with embeddings Feedly Summary: llm-gguf 0.2, now with embeddings This new release of my llm-gguf plugin – which adds support for locally hosted GGUF LLMs – adds a new feature: it now supports embedding models distributed as GGUFs as well. This means you can…

  • Simon Willison’s Weblog: TextSynth Server

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    Source URL: https://simonwillison.net/2024/Nov/21/textsynth-server/ Source: Simon Willison’s Weblog Title: TextSynth Server Feedly Summary: TextSynth Server I’d missed this: Fabrice Bellard (yes, that Fabrice Bellard) has a project called TextSynth Server which he describes like this: ts_server is a web server proposing a REST API to large language models. They can be used for example for text…

  • Hacker News: Meta Uses LLMs to Improve Incident Response

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    Source URL: https://www.tryparity.com/blog/how-meta-uses-llms-to-improve-incident-response Source: Hacker News Title: Meta Uses LLMs to Improve Incident Response Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses how Meta has employed large language models (LLMs) to enhance its incident response capabilities, achieving a noteworthy 42% accuracy rate in identifying root causes of incidents. This innovative approach…

  • Hacker News: Batched reward model inference and Best-of-N sampling

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    Source URL: https://raw.sh/posts/easy_reward_model_inference Source: Hacker News Title: Batched reward model inference and Best-of-N sampling Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses advancements in reinforcement learning (RL) models applied to large language models (LLMs), focusing particularly on reward models utilized in techniques like Reinforcement Learning with Human Feedback (RLHF) and dynamic…

  • Hacker News: Llama 3.1 405B now runs at 969 tokens/s on Cerebras Inference

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    Source URL: https://cerebras.ai/blog/llama-405b-inference/ Source: Hacker News Title: Llama 3.1 405B now runs at 969 tokens/s on Cerebras Inference Feedly Summary: Comments AI Summary and Description: Yes Summary: The text discusses breakthrough advancements in AI inference speed, specifically highlighting Cerebras’s Llama 3.1 405B model, which showcases significantly superior performance metrics compared to traditional GPU solutions. This…

  • Simon Willison’s Weblog: Quoting Jack Clark

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    Source URL: https://simonwillison.net/2024/Nov/18/jack-clark/ Source: Simon Willison’s Weblog Title: Quoting Jack Clark Feedly Summary: The main innovation here is just using more data. Specifically, Qwen2.5 Coder is a continuation of an earlier Qwen 2.5 model. The original Qwen 2.5 model was trained on 18 trillion tokens spread across a variety of languages and tasks (e.g, writing,…

  • Hacker News: You could have designed state of the art positional encoding

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    Source URL: https://fleetwood.dev/posts/you-could-have-designed-SOTA-positional-encoding Source: Hacker News Title: You could have designed state of the art positional encoding Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses the evolution of positional encoding in transformer models, specifically focusing on Rotary Positional Encoding (RoPE) as utilized in modern language models like Llama 3.2. It explains…