Gemini 1.5 Pro has entered the (LMSys) Arena! Some highlights: -The only "mid" tier model at the highest level alongside "top" tier models from OpenAI and Anthropic -The model excels at multimodal, and long context (not measured here) -This model is also state-of-the-art
LLMS
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Running Meta-Llama-3-8B-Instruct with LLM CLI Tool
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Yes, you can run prompts like this: llm -m Meta-Llama-3-8B-Instruct -o temp 0.1 "3 names for a pet rhino" https://
github.com/simonw/llm-gpt
4all?tab=readme-ov-file#model-options
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Extended Base Model Development and Implementation
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For clarity, I extended the base model — not the instruct version, so this is expected.
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Claude Hack: Grammar Structure Works for All LLMs
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Yes! For sure try it with Claude, it's essentially a Hack for all LLMs, are it's dealing with grammar and how to structure sentences on a general level, which all LLMs will understand.
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ChatGPT Hack: Dependency Grammar for Humanizing Text
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ChatGPT Hack: Tired of AI generated content that sounds too much like ChatGPT? Use Dependency Grammar Framework in your prompts. It changes the output to sound 100% like a human. Follow the thread:
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Custom GPTs Updated with Dependency Grammar Framework
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I just updated my Custom GPTs with Dependency Grammar Framework! You can test them out, but I already see content output as 100% human written: – Sales Email Generator GPT: https://
godofprompt.ai/gpts/sales-ema
il-generator
… – SEO Article Generator GPT: https://
godofprompt.ai/gpts/seo-artic
le-writer
… – Article Rewriter GPT: -
Phi Training Approach Criticism: Quality Data vs Quantity Debate
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in my opinion, the Phi approach to training language models is just wrong • i'm not convinced that training on less (albeit "higher-quality") data is better than training on as much data as possible
• i'm not convinced that training on synthetic data ever works better than -
Evaluating Speed Cost and Offline AI Performance Metrics
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Speed, cost and the ability to run offline on a personal device are the things I care most about I still don't have a great answer for how to best evaluate these things but I'm researching that at the moment
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NVIDIA Hopper leads generative AI performance in MLPerf benchmarks
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NVIDIA Hopper takes lead in Generative AI on MLPerf! See https://
nvda.ws/3J1knIW In the latest (4th) round of #MLPerf performance benchmarking – the 'gold standard' for #AI workload #testing – the formidable Llama 2 70B and Stable Diffusion XL are center stage -
GPT-5, Gemini 2.0, and the race for LLM advancement
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I see a lot of comments on how much is riding on GPT-5 to show LLMs haven’t plateaued (I have said similar). But it isn’t like OpenAI is the only company expecting future big model improvement. We know Gemini 2.0 is in the cards, and we know Anthropic & X are training new models.