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Mana

@manatheturipa

Maori AI developer and Researcher and Gamer hehe Call of the Daddy

GitHub
GitHub

Joined January 2026

16 Following64 Followers29 Apps
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Published apps

  • BHS Ultimate HeadSwap & FaceSwapBased on BFS - Best Face Swap, VisoMaster, and SwapAnyHead.
  • MuseTalkMuseTalk is a cutting-edge video-to-video (V2V) lip-sync solution engineered to deliver highly accurate and natural mouth movements synchronized to audio input. Precision LipSync: Realistic and seamless synchronization of speech audio to facial movements. Efficiently designed to run on 8–12 GB VRAM,
  • REAL-Video-EnhancerInterpolate, Upscale, Decompress, and Denoise videos Locally on Linux/Windows/MacOS.
  • FaceswapDeepfakes Software For All
  • LatentSyncHigh quality LipSync Application with a simple UI
  • AI Video Clipper & LoRA CaptionerAutomatically clip videos and generate captions for LoRA training using advanced vision models like Gemma-3, Qwen3-VL, and Qwen2-VL.
View all apps
Posts · 6
Mana@manatheturipa·13dEdited
🚀 Automated LoRA Studio — turn your videos into custom motion LoRAs. Upload a video, choose a supported Wan or LTX model, describe the movement, and click Prepare + train. The app automates: - ✂️ Cutting and formatting training clips - ✅ Frame count, size and FPS checks - ✍️ AI captions you can review and edit - ⚙️ Training caches and trainer setup - 💾 Checkpoints, resume, supported previews and export It brings together work you’d otherwise split between AI Video Clipper, manual FFmpeg commands, captioning tools and separate Wan/LTX training interfaces. No coding or manual training configs needed for the built-in workflow. Designed to make video LoRA creation approachable without technical experience. Free and open source. Your footage stays local. Compatible training hardware required. 👉 Get github.com/manat0912/automated-…
github.comGitHub - manat0912/automated-lora-studio: Pinokio launcher for Automated LoRA Studio: NVIDIA CUDA and supported AMD ROCm on Windows/Linux, CPU preparation on Apple Silicon macOS.Pinokio launcher for Automated LoRA Studio: NVIDIA CUDA and supported AMD ROCm on Windows/Linux, CPU preparation on Apple Silicon macOS. - manat0912/automated-lora-studio
Automated LoRA Studiomanat0912/automated-lora-studio
#lora
Mana@manatheturipa·14d
Pinokio activity

New on Pinokio

Automatically discovered via GitHub

Automated LoRA Studiomanat0912/automated-lora-studio
Mana@manatheturipa·4mo ago

AudioChunker

Audiochunker — slice any audio into perfectly timed clips, instantly Audiochunker is a lightweight Pinokio app that takes any audio file and chops the whole thing into fixed-length clips with one click. Drag in a track, pick a length on the seconds slider (10 / 20 / 30 / 40 / 50 / 60s), and it splits the entire file into back-to-back segments — then export them all at once as a single .zip, or grab any clip on its own. What it's built on ffmpeg under the hood (segment muxer with stream copy -c copy) — so clips are cut without re-encoding and keep the source's exact codec and quality. No qualit

Audiochunkermanat0912/audiochunker
5
Mana@manatheturipa·4mo ago

animated portrait Avatars with low vram support

FastLive Pinokio delivers high‑impact real‑time facial animation with built‑in streaming straight from the app, powered by a Unity video driver for smooth, low‑latency output. Optimized to run on systems with 12GB of VRAM, it brings pro‑level performance to creators who want fast, clean, production‑ready results without the overhead.

FasterLive-Pinokiomanat0912/FasterLivePinokio
2
Mana@manatheturipa·4mo ago

Hyperframes now has gradio UI

HyperFrames is an open-source framework that transforms HTML, CSS, media, and seekable animations into deterministic MP4 videos. It can be used locally via the CLI, integrated with AI coding agents through LM Studio or Olama, or serve as the rendering core for hosted authoring workflows. I also built a Gradio interface so people can easily add video and audio inputs for rendering.

hyperframes-studiomanat0912/HyperFrames-Studio
2
Mana@manatheturipa·5mo ago

help from devs to improve FluxRT

I’ve completed a full installer for FluxRT and have already integrated several new modes into the UI, including Cam‑to‑Live Stream, Image‑to‑Image, and Image‑to‑Video. The interface and installer are stable, but the application logic and model behavior still need refinement. I’m looking for developers with strong experience in Flux‑based architectures, model debugging, and runtime optimization to help resolve remaining issues and improve overall performance. Specifically, I’m seeking someone who can assist with: Diagnosing and fixing inconsistencies in Flux model outputs Improving stability ac

FluxRTmanat0912/-fluxRT-installer
1
You’re all caught up.
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