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fffiloni 
posted an update 1 day ago
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Carbon-X brings DNA and language together: it reads sequences and answers questions about them 🧬

To accompany the release article, I put together Carbon-X Playground: five experiments exploring sequence completion, single-letter changes, regulatory roles, DNA origins and motif finding.

Try curated samples or your own sequences, ask questions and compare answers with references when available.

Built with Gradio, running on ZeroGPU.

📖 HuggingFaceBio/Carbon-X-Release
🧬 fffiloni/Carbon-X-Playground
Nymbo 
posted an update 8 days ago
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Introducing Live Subtitles, a Windows tray app that captions anything your PC is playing and isn't butt ugly. live and fully local. It runs NVIDIA's Parakeet-unified 0.6B on your GPU, puts words on screen about 0.36 s after they're spoken, and uses less than one CPU core while it does it.

I built a benchmark for it out of real TV, podcasts, earnings calls and a short film. Parakeet-unified scores 12.1% WER there, close to Nemotron streaming's 11.4%, but with much better punctuation and lower worst-case delay. Once a caption is on screen it never gets rewritten or jumps lines, and the overlay disappears when nobody's talking.

No NVIDIA GPU? It falls back to Nemotron on the CPU, which also covers 30 other languages. It can also write SRT/ASS/VTT files for videos on disk.

Windows only. The GPU engine needs an NVIDIA card with ~3.2 GB of free VRAM. MIT.

Edit: the first version of this post said 13.8% vs 17.0%. The replies caught a scoring bug (numbers weren't normalized), so the benchmark now uses Whisper's English normalizer and the numbers above are re-scored.

Get it here:
https://github.com/Nymbo/Live-Subtitles

Models:
nvidia/parakeet-unified-en-0.6b
nvidia/nemotron-speech-streaming-en-0.6b
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fffiloni 
posted an update 13 days ago
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📖 A gamebook you can play in your own words, powered by local Decision Models.

Traditional gamebooks offer explicit branches: “To enter the forest, turn to page 42.” In Choose your own adventure, you can describe an action, question a character, or ask what you already know before deciding. Clickable choices remain available.

The story’s branches and consequences are authored. Natural language adds a flexible way to interact with them, with conversations between actions.

I built this project to explore a concrete role for Decision Models in an interactive application:

• Kev-4B makes structured decisions: matching intentions to available actions and distinguishing acting from discussing.
• Ink manages story progression, discoveries, inventory and endings.
• Qwen3-8B selects dialogue responses from authored content available in the current state.

Both models run locally inside the Space through llama.cpp, using quantized GGUFs. You can inspect the model calls, scores and routing decisions directly in the interface.

The current release includes three adventures in French and English, with a pack format for adding new stories without changing the engine.

It’s still experimental, and interpretations can go wrong. I’d love feedback on how it feels to play—and on this use of Decision Models to connect natural language with explicit game logic.

Try and play here: fffiloni/choose-your-own-adventure-dm 🤗
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fffiloni 
posted an update about 1 month ago
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Been pushing Viggle Animate a bit further 👀

Viggle Mine is my take on longer, harder character replacement shots — crowds, distance changes, characters turning their back and reappearing.

Still experimental, but it’s getting surprisingly robust.

Try it : fffiloni/Viggle-Mine 🤗
fffiloni 
posted an update 2 months ago
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If an agent can build the obvious demo, the obvious demo probably isn’t worth building anymore.
For years, turning a research repo into something people could actually try was valuable by itself.
That part is becoming automated — and that’s a good thing.

Which means the interesting work moves elsewhere: finding the weird use case, the right interaction, the unexpected model combination — or simply knowing which paper is worth anyone’s attention.

The demo used to be the product. Now it needs a point of view.
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Nymbo 
posted an update 3 months ago
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Anthropic gave me six months of Claude Max 20x through the Claude for Open Source program, granted based on my Hugging Face work. Thank you
Anthropic
for supporting open source.

So far I've been pointing it at Markdown Minimap, an Obsidian plugin that adds a scrollable IDE-style minimap to your notes. This week I've been clearing a backlog of user-reported issues on it, with Claude often handling them end to end.

https://github.com/Nymbo/Markdown-Minimap — issues and PRs welcome.
julien-c 
posted an update 3 months ago
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who's working on an NVFP4 version of Kimi-K3?
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Nymbo 
posted an update 3 months ago
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Introducing Inflect-v2, two exceptionally small, open-weight English TTS models at just 3.9M and 9.3M parameters. Both generate speech multiple times faster than real-time on CPU. Despite their size, Inflect-v2 delivers quality that is competitive with much larger lightweight TTS systems, including KittenTTS, Piper, and Supertonic-3.

CPU, CUDA, PyTorch, and ONNX are supported. Apache 2.0.

See it for yourselves:
owensong/Inflect-Micro-v2
owensong/Inflect-Nano-v2

Try the Demos:
Nymbo/Inflect-TTS (unlimited CPU usage)
owensong/Inflect-v2 (ultra-fast ZeroGPU usage)
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fffiloni 
posted an update 4 months ago
fffiloni 
posted an update 4 months ago
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I made a Hugging Face Space for SCAIL-2 🤗

Reference character + driving motion → animated result.

A simple demo to explore the paper’s core workflow with curated examples.

👉 fffiloni/SCAIL-2
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fffiloni 
posted an update 4 months ago
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⏱️ Built a small Space for Visual Chronometer / Pulse of Motion.

Upload a video and estimate its Physical FPS: the frame rate implied by visual motion, independent of metadata.
Useful to inspect “chronometric hallucination” in generated videos: clips that look smooth, but move with the wrong physical time scale.

Try it here: fffiloni/Pulse-of-Motion
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