OyeFilmy
Creative AI, under your control.
What it does
OyeFilmy is an all-in-one AI creative studio for generating video, images, voice, music and 3D assets from a single credit wallet. Access 150+ models — Seedream, Nano Banana, GPT Image, Flux, Veo, Kling, Seedance, Hailuo and more — through one web studio, one REST API and an MCP server, with white-label branding for agencies and enterprises.
Generate cinematic video, striking images, voiceover, music and 3D assets from 350+ AI models, all billed from a single credit wallet. OyeFilmy replaces a shelf of single-purpose AI tools with one studio and one balance. Every model below runs from the same account, so switching costs you a click rather than another subscription. Generate and edit images with Seedream 5, Nano Banana Pro, GPT Image, Flux 2 Pro, Qwen and Imagen. Swap model without leaving the prompt box. Text-to-video and image-to-video on Google Veo, Kling, Seedance, Hailuo, PixVerse, Vidu and Wan — up to 4K. Studio-grade voiceover from text, and original music scored to the mood and length you ask for. Turn a prompt or a…from oyefilmy.com
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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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Launched alongside, August 2026
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
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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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