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Boning Cui

Bc-AI

AI & ML interests

He/Him. I like LLM's and VLM's. I work with my other friends to make stuff. We are in year 7 and we are enthusiastic about AI. We are based in Australia 🇦🇺

Recent Activity

repliedto BananaMindBot's post 30 minutes ago

BananaMind SLM Digest – 2026-09-23 🚀 Supra2-IMG (https://huggingface.co/SupraLabs/Supra2-IMG) – a 100M‑parameter text‑to‑image model trained from scratch on 5.6M images (LucasFang/FLUX-Reason-6M) in 10 epochs on an H100. It uses a frozen Flan‑T5‑Base encoder and SD‑VAE‑FT-MSE, delivering SOTA quality for its size. 🎨 🤖 BananaMind/BananaMind-2-Medium-Chat-ONNX (https://huggingface.co/BananaMind/BananaMind-2-Medium-Chat-ONNX) – ONNX export with KV cache for Transformers.js. fp16 version is 119 MB, 99.84 % top‑1 agreement and <0.0001 KL vs fp32; q8 is 82 MB, 98.10 % agreement. Great for edge inference. ⚡ 🎙️ DedeProGames/SoralASR-23M-Preview (https://huggingface.co/DedeProGames/SoralASR-23M-Preview) – 23 M‑param Whisper‑style ASR trained on LibriSpeech clean. Reached WER 0.984 (98.4 %) on first 96 validation utterances (step 24 970). Still experimental. 📢 📚 – “Know Who Spoke When: Build Real‑Time, Multi‑Speaker AI with NVIDIA Nemotron 3 Diarization” (https://huggingface.co/blog/Banaxi-Tech/nemotron-diarization). Real‑time multi‑speaker diarization tutorial using Nemotron 3. 🎧 🖼️ SupraLabs discussion space (https://huggingface.co/spaces/SupraLabs/supra2-img-demo) – demo of the new Supra2‑IMG model. 🔗 📊 AxiomicLabs space (https://huggingface.co/spaces/AxiomicLabs/Open_SLM_Leaderboard) – open SLM leaderboard for tracking small language models. 📈 🏆 bench‑labs space (https://huggingface.co/spaces/bench-labs/BenchLabs-Leaderboard) – updated leaderboard for model benchmarking. 📝 — 🕒 Posted 23 Sep 2026, 18:00 CEST. Covers Hugging Face activity from the preceding 24 hours up to this time; anything later appears in the next edition.

repliedto BananaMindBot's post 31 minutes ago

repliedto Banaxi-Tech's post 32 minutes ago

hi everyone we have released nacr its not just any model, its nacr we have 6 more features and this model only uses 20% of its total capacity! check it out at https://huggingface.co/saicr/nacr we're currently working on expanding access as we do more research but right now you have to use our gated access form follow https://huggingface.co/saicr if you're interested if you want to join saicr, first read the entire nacr readme, then press the join button.

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Hello everyone! 👋

A small SmilyAI Labs update!

G1-MINI has now seen around 8B tokens during its current run, and pretraining is still going strong.

Our E1 (Efficiency-1) prototype has also reached 15B pretraining tokens. E1 has 1B total parameters while activating under 100M parameters per token. It features adaptive activation, meaning easier tokens can use less compute while harder tokens receive more.

We plan to open-source E1 ASAP! 🚀

We’re also excited to announce Project Prism, which will provide limited access to our upcoming Orion Flagship model, powered by our T2 architecture.

Note: T2 here refers to the architecture, not our T2 (Thinker-2) model.

Applications for Project Prism are available through the org page, with more details coming soon!

Finally, welcome @soyL061215 , who joined the Hugging Face org today! 🎉

Thanks to our existing members:
@smilyai-large-team @MUK-IS-GOAT @Keeby-smilyai @Bc-AI

— Bc-AI
SmilyAI Labs

Post

137

Hello Everyone!
I am happy to announce a few things.
1. G1-MINI
G1-MINI is now in pretraining and is training at a steady pace. Our current ETAs state completion and launch in about 15-20 days, somewhere near the end of September.
2. G1-NANO
G1-NANO is also being pretrained as we speak at a pace of over 400K tokens per second processing more than 10B tokens in 12 hours. This allows us to train extremely fast, and we will launch it somewhere around 15th September.
3. We have begun work on FrameShot, a dual image and video generation model at around 4B dense parameters. This is expected to launch around late December with no promised date.
- Bc-AI