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whybe-choi  authored a paper 10 days ago
KoViDoRe: A Benchmark for Korean Visual Document Retrieval
whybe-choi  authored a paper 10 days ago
KoVRE: Training an Efficient Embedding Model for Korean Visual Document Retrieval
cppraii  updated a model 4 months ago
pseudolab/GR00T-N1.7-3B-OMX-PickupDolls-2Cam
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Tonic 
posted an update 7 days ago
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👋Hey there folks ,

I wanted to use a Jev model in a practical way , and I came up with this OCR pipeline using decision-models to evaluate OCR quality .

Check it out :

Tonic/OCR-with-JEV
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whybe-choi 
authored 2 papers 10 days ago
Nymbo 
posted an update 22 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
  • 7 replies
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cetusian 
posted an update about 1 month ago
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Surogate Speech is out 🐇 small open speech models for agents, the speech side of Surogate.

First language shipped is Romanian, and the numbers came out better than I expected: 5.69% WER on FLEURS with a 116M model. Canary 1B gets 5.95% on the same clips, Whisper large-v3 8.42%. Leaderboard runner, one RTX 5090.

What's in it:

🎧 jackrabbit-110m-ro: speech recognition, 2,500× real time on one GPU
⚡ jackrabbit-110m-ro-streaming: live, final text about 0.7 s after you stop talking
🗣️ amami-357m-ro: TTS with three voices, runs on a CPU

Serving is one line with our engine: surogate serve --stt surogate/jackrabbit-110m-ro

Transcripts for every clip are public if you want to rescore it.

surogate/surogate-speech-6ab680eb84c7ff75fb73ad5a
https://github.com/invergent-ai/surogate-speech
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.
Nymbo 
posted an update 4 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)
  • 6 replies
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cppraii 
updated a model 4 months ago
cppraii 
published a model 4 months ago
juyoungml 
authored a paper 4 months ago
cppraii 
updated a model 4 months ago
cppraii 
published a model 4 months ago
LeoKimDowny 
updated a dataset 4 months ago
cetusian 
posted an update 4 months ago
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most labs won't bother teaching a small model to write and think in real romanian. no invented words, no english leaking in mid-sentence, diacritics intact.

we did.

surogate 3.5 is out. 2B and 4B, apache 2.0. invented word-forms cut from 4 per 1k down to ~1.5, and it reasons in the language you prompt it in, every time.

intelligence should speak your language too.

the models:

surogate/Surogate-3.5-4B

surogate/Surogate-3.5-2B
kinam0252 
submitted a paper to Daily Papers 4 months ago
LeoKimDowny 
published a dataset 5 months ago
LeoKimDowny 
updated a dataset 5 months ago
LeoKimDowny 
published a dataset 5 months ago
yunihg 
updated a dataset 5 months ago
yunihg 
published a dataset 5 months ago