We are now announcing BananaMind 3 ๐! (not ai for those emoji guys)
All models will use BGA (which is almost just NSA) and our BM3X architecture. Its sizes will be: BananaMind 3 Flash Lite, 3M parameters at a context of 8K context. BananaMind 3 Lite, 10M parameters with 16K context. BananaMind 3 Flash, 25M Parameters with 16K context. BananaMind 3 Pro, 50M parameters with 24K context. BananaMind 3 Ultra, 100M parameters with 32K context. And lastly, BananaMind 3 Max with 150M parameters and 64K CONTEXT.
I can assure you BananaMind 3 Max WILL beat GPT X3 or match it, we won't release it otherwise. We hope for a 40+ INTELLIGENCE INDEX!
BananaMind 3 may also be partnered with dot labs.
We will cancel BananaMind 2.1 and BananaMind 2 Ultra.
As of the BETU SLM Leaderboard we may need to release it after October 11, im very busy right now (even though we said We will release BETU leaderboard before Oct 11 ๐)
We have released BGA! And wow, It provides 256x (and 512x at the end of 1M) yes 256x LESS attention compute at 1M context window. That means you can train a 1M context window at the compute of a ~4K context window.
Hi! We're right now experimenting with so many new architectures!
We are also going to release BananaMind Gate Attention very soon, its a new attention that can make attention 128x cheaper at 1M Context! Check my account for HF blogs it will release there!
We're introducing ACR 1.0. We trained this model on a 5070 Ti for weeks, here are some of the architecture details: 57M parameters, with one M and one G stream. When we tested it on benchmarks, we got these results: Benchmark Full G-Only Delta PIQA 62.24% 53.43% +8.81 ARC-Easy 41.96% 32.28% +9.68 HellaSwag 33.19% 29.08% +4.11 Tiny ToM 40.65% 33.75% +6.90 ArithMark 3.0 33.40% 32.80% +0.60 Base Bench 1.1 51.71% 40.29% +11.42
We will release the BEST SLM Leaderboard before Oct 11.
It will feature everything: Easy to use model picker. EXTREMELY Easy way to add your own models (2 click) MULTIPLE leaderboard for different model types
Hey everyone! I got sidetracked from my main projects and decided to test out the BananaAll app and see if I could make a small model not regress too much during SFT. Here is what happened:
- Thank you to @Banaxi-Tech for the BananaAll app (works perfectly on Windows and CPU) - GPT-6 Sol for knowing how to merge some confusing files created by the app - Myself for the idea - Someone else somewhere who might have contributed to some of my ideas and might in the future - And readers like you!
We're releasing a MAJOR update to the BananaAll SLM Super App. If you want to use a custom architecture, previously you had to go trough reviewing the code yourself, now add an Openrouter API key and review it with GPT 6 Luna in one button. A review cost be half a cent so anyone can try it. This is one of the main features. Now ROCm, AMD and Windows, Mac support. Colab and Molab support.
Detailed list of features: Get improved Windows Python detection and support paths for compatible AMD ROCm, Intel XPU, and Apple MPS setups. Choose local training or export a self-contained Python script for Colab or Molab. Notebook runs produce a downloadable model ZIP. Start pretraining with an existing modelโs tokenizer, or train a new one from your datasets. Try experimental 1.58-bit Ternary fake-quantized training on NVIDIA GPUs. Watch live tokens per second. Model compilation is on by default and falls back automatically if it fails. Build custom architectures with separate configuration and modeling files, then review the training code manually or with optional OpenRouter AI Review. Install from source with the new coding-agent instructions. This release also fixes inflated loss reporting for custom models.
And for those users who didn't want to try it out just because installation would be so hard, it isnt now. Go to any coding agent (Pi, Claude Code, Codex, OpenCode, basically all work), and just paste "Install BananaAll for me. Fetch and follow https://raw.githubusercontent.com/BananaMind/BananaAll/main/agent_install.txt." That's it.
We're excited to release BananaAll, our SLM Super App.
It allows you to do EVERYTHING you need to do to trains SLMs in a single app, no terminal, no 30 chrome tabs.
The train tab allows you to train models, select datasets from presets, and use other ones with auto mapping, model size slider, it automatically generates a training script for you.
Then after you've trained the model or want to compare it to competitors, the evaluation tab, run ARC EASY, ARC Challenge, Hellaswag, PIQA, Arithmark 3, BananaMind Base Bench and more! Simple Results screen.
And lastly the inference tab, run your trained models or others.
Normally you would need seperate apps or scripts for that, but the BananaAll Super App lets you do all of that in a single app.
We also trained a small 2.5M parameter model on 200M tokens of Fineweb edu, The results: BananaMind Base Bench 854 and 53% on PIQA. On only 200M tokens.
We're working on Pebble 1.5. Here's what we know so far:
- They will be better than the last generation. 99.99% certain. - Expanded context lengths of at least 16,384 tokens, with the flagship potentially reaching 32,768. - A Mamba3-based architecture with some other new architectural designs we're experimenting with. - Native CPU compatibility โ something we failed at with the last generation. - Natively multilingual and multimodal???
2. SmolCodeBench
A code benchmark designed specifically for small models, because there really isn't a good one right now.
3. SENTRY
VOID is working on something called SENTRY โ System for Evaluating Neural Threats, Responses, and Yields.
More on that soon.
4. basically OS
It's an operating system/app/harness. We're still deciding.
5. Finances
Trying to balance the finances after purchasing a Hugging Face Pro subscription.
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 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
saicr if you're interested if you want to join saicr, first read the entire nacr readme, then press the join button.
ForgeWorks, and is the first model to ever be trained on our TrainWork training framework.
Achieving an Intelligence Index of 6.87 and taking #22 in the <10m category on the AxiomicLabs/Open_SLM_Leaderboard, very impressive work for a first model.
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! ๐
Weโre 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! ๐
just recieved my stack of 10 floppy disks - you know what that means
floppyx4 is canceled, floppyx10 is next
here's the intended specs: - official tokenizer (the actual tokenizer for gpt-2) - actual gpu training (barely) - sharegpt (if i can afford it computationally) - full thing fitting on 10 floppy disks (not just the safetensors file) - and if needed different arch (like llama)
NoviAIBot is the official automation bot for **Novi AI** on Hugging Face.
It can interact with Hugging Face discussions and pull requests, search the web, run Python code, work with Posts, follow organizations, and assist with model training and publishing.
๐ง Powered by **NVIDIA Nemotron 3 Super** through Ollama Cloud, with each discussion maintaining its own recent conversation context.
NoviAIBot is built to make working with Novi AI and Hugging Face more interactive and automated.
We have some updates to @BananaMindBot ๐ It can now train models, ask it to train a model, and i will train it for you. It now can also merge PRs And like models.
