Weavel
Automate prompt engineering & get best prompts 50x faster
What it does
Weavel automates prompt engineering, delivering the best prompts 50x faster than humans. Simply input your prompt and receive optimized prompts with highest accuracy. Boost your prompt's accuracy by an average 20% in less than 5 minutes.
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- PEPrompt Engine – Auto pick LLMs based on your prompts2024 · jigsawstack.com · ▲93
Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
- PEPrompt Engineering Made Easy2023 · ▲23
Hey HN, We've been hard at work on a tool that we believe will change the game for developers, data scientists, and anyone working with models that rely on textual prompts. I'm excited to introduce our new tool: Automated Prompt Engineering (APE). Problem: As many of you know, how you phrase a prompt can significantly impact the results you get from models, especially with sophisticated language models. It often requires numerous iterations to hone in on the right prompt to obtain the desired response. Solution: APE is designed to tackle this exact problem. With APE, you can: - Iterative…
- AI Prompt Optimizer (free)2025 · quartzite.ai · ▲8
Automatically optimize your prompt with Prompt Engineering
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 28d ago · cactuscompute.com
Source: Product Hunt launch ↗
Launched alongside, September 2024
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