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fffiloni 
posted an update 1 day ago
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139
I’ve been building IDOL Commons 🗿

A place to create, share and explore 3D Gaussian splats, powered by IDOL from Sperid Labs.

Start with an image, or generate one from a prompt. Inspect the result in 3D, choose its thumbnail, add a description and credits, then decide whether to publish it to the community collection.

Browse what others have shared and download the original PLY files, with attribution and per-object licensing.

I’d love to see what you contribute — and hear what would make this useful in your workflow.

Try it:
fffiloni/idol-commons

Community dataset:
fffiloni/idol-community-assets
Tonic 
posted an update 1 day 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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loubnabnl 
posted an update 3 days ago
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𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 🧬 𝐅𝐢𝐧𝐞𝐃𝐍𝐀: 𝐭𝐡𝐞 𝐛𝐞𝐬𝐭 𝐝𝐚𝐭𝐚𝐬𝐞𝐭 𝐭𝐨 𝐭𝐞𝐚𝐜𝐡 𝐚𝐧𝐲 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐦𝐨𝐝𝐞𝐥 𝐃𝐍𝐀.
Training Qwen3-14B on it produces Carbon-X, the strongest open model on DNA benchmarks, on par with GPT-6.1 Sol.

It contains:
- Midtraining: 300B+ tokens of genomic sequences, papers and web pages mixing DNA with text
- SFT: 200K samples, from variant effect prediction to sequence question answering
- RL: 98K prompts with verifiable rewards

Data, models and the full recipe are open.
HuggingFaceBio/FineDNA

Enjoy this late Halloween treat! 🎃
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fffiloni 
posted an update 10 days 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
nielsr 
submitted a paper to Daily Papers 14 days ago
Nymbo 
posted an update 17 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 23 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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AtAndDev 
posted an update 24 days ago
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@Banaxi-Tech stop hiding my comments. AND STOP STEALING PAPERS AND SPREADING MISINFORMATION.
your BGA blog is a copy of NSA (deepseek, 2025) branded under your name. literally the same top16 selected blocks, 512 local window, router over block summaries, all you did was change block size from 64 to 128.
you didnt cite NSA once but you put a “please cite BGA” bibtex at the bottom.
i commented under your post and said that there is no way that you can support claims like: “The Accuracy Should BE WAy better than DSA but untested yet.” you didnt run a single experiment. and the 256x isnt from BGA, its just n/2k with k=2048 so the exact same k DSA uses. if opus wrote this for you, at least read it before posting.
i commented again after you hid my comment despite it having constructive and correct feedback and you hid that too. and again.
you can hide the truth and just try to get hf post likes..... but is it really the thing that needs to be done? do you really want to take papers and make them yours while barely even changing the params?

admitting your mistakes and doing something about them needs humbleness, intelligence, humanness.
i encourage you to admit your mistakes and try to do better next time (at least read what blog your ai wrote or do proper experiments to back your stuff up).
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sbrandeis 
posted an update 25 days ago
sbrandeis 
posted an update about 1 month ago
nielsr 
submitted a paper to Daily Papers about 2 months ago
mrfakename 
posted an update about 2 months ago
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2,637
We’ve been working with LAION on a voice acting arena. You listen to two models doing the same scene and compare how well they pull it off.

It’s ready to try now - would love to hear what you think 🙂

TTS-AGI/voice-acting-arena
fffiloni 
posted an update about 2 months 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 🤗
AtAndDev 
posted an update 2 months ago
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SPECK 2 IS ALREADY OUT: specklabs/Speck2-140M

Pretrained on 4x more tokens than the previous releases (20b vs 5b).
Instruct tuned versions are coming soon.
Very interesting models are coming soon too (hint: super long context).

Thanks for everyone supporting!
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AtAndDev 
posted an update 2 months ago
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SPECK1.5 IS COMING SOON!
Same 5B token budget but much better corpus quality.

Also getting a ton of downloads, thanks for everyone downloading and liking <3

specklabs
AtAndDev 
posted an update 2 months ago
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NEW SPECK UPDATES:

Just hit #14 and #15 with out FIRST models on Open SLM Leaderboard. The models were trained on 5B tokens, while competing with similarly sized models trained on more than 6-20x the data.

A new base model Speck1.5-140M being trained right now on a higher quality corpus and will be released soon.
SpeckChat3 is coming very soon with 1 million samples, specifically designed to post train small base models.

Also, just to clarify stuff, we will NOT release anything that is NOT MIT licensed EVER. Openness is needed in small language research.

Thanks to everyone supporting the project, and stay tuned for new releases!
AtAndDev 
posted an update 2 months ago
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SPECK UPDATES:
1 New instruct model tuned on top of Speck1-140M: specklabs/Speck1-140M-Instruct
2 Instruction tuning datasets
2 GGUFs

Much more coming soon:
Speck1.1-140M-Instruct that is post trained on SpeckChat2 will be coming very soon
New base model Speck1.5-140M is coming with a much higher quality corpus

Thanks to everyone who is already supporting the project, and stay tuned for new releases!
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nielsr 
submitted a paper to Daily Papers 2 months ago
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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AtAndDev 
posted an update 2 months ago
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FIRST SPECK MODEL RELEASED:
specklabs/Speck1-140M

new models coming very soon (both instruct and much better models), with much much higher training scale as i am getting marenostrum5 access soon!
we will be looking at 100b-2t token budgets :)
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