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Banaxi-Tech published a model 1 day ago

hugging-models-community/start_discussions_here

Banaxi-Tech updated a Space 1 day ago

hugging-models-community/README

Banaxi-Tech published a Space 1 day ago

hugging-models-community/README

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posted an update about 5 hours ago

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41

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.

Check IT OUT: BananaMind/blog

The Accuracy Should BE WAy better than DSA but untested yet.

And, now some updates on BananaMind 3:

BananaMind 3 Will start training Soon!
Sizes: 10M, 25M, 50M, 100M, 150M

And the context windows ARE INSANE: 10M, 16K context, 25M 16k context, 50M 32K context, 100M and 150M, 64K context!!!!

3 replies

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posted an update 1 day ago

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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!

published a model 1 day ago

hugging-models-community/start_discussions_here

Updated 1 day ago

updated a Space 1 day ago

README

published a Space 1 day ago

README

posted an update 2 days ago

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74

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

Check it out at saicr/ACR-1.0

3 replies

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posted an update 3 days ago

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Its SAICR time tomorrow.
Get ready!

28 replies

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posted an update 4 days ago

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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

And more!

So why don't you help us build it?

Join

betu-slm-leaderboard-testers

3 replies

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posted an update 8 days ago

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ACR 1.0 launch is being prepared and researched now!
Also I'm going to vacation tomorrow but it should still be released!

3 replies

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posted an update 12 days ago

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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 model’s 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.

Check it out at https://github.com/BananaMind/BananaAll/

Also on SAICR, we're currently training a new major model (NACR v2) and ACR 1.0 is in the finishing.

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posted an update 14 days ago

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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.

Check it out at https://github.com/BananaMind/BananaAll.

25 replies

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posted an update 15 days ago

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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.

14 replies

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posted an update 16 days ago

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saicr is going to have its first model launch around October 2.
We're working so hard to get the models available as soon as possible.

7 replies

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posted an update 17 days ago

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This day is Sol nice.

posted an update 17 days ago

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🚀 **Introducing NoviAIBot!**

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.

🧠 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.

**The bot is now live.** 🤖

→ @NoviAIBot

44 replies

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posted an update 18 days ago

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We have some updates to @BananaMindBot 🍌
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.

28 replies

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posted an update 19 days ago

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We've released @BananaMindBot .

Most things you do on HuggingFace, BananaMindBot can do. Fast

Mention @BananaMindBot on a model, dataset, Space discussion, paper, blog comment, or top-level post and it'll reply there.

It's powered by North Code Mini (Qwen3.8 27B, with GPT OSS 120B as fallback).

A few things it can do:

Search for models and datasets
Look up users and orgs and see what they've published
Read model cards, configs, dataset files, blog posts, and org profiles
Answer questions about what it finds
Write and run its own code in a locked-down sandbox when it needs to verify something
Check things like a model's real parameter count from the safetensors headers instead of just repeating the model card
Remember something for later if you explicitly ask it to
Forward a message to @Banaxi-Tech
Post a daily roundup of developments in the small-language-model space

It won't execute code you give it. It can read and review that code, but anything it runs is code it wrote itself.

It also can't access private data or credentials.

Mention it somewhere.

It's going to also find this post!

(Some parts inspired by CompactBot and @CompactAI Follow them please)

37 replies

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posted an update 20 days ago

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We're introducing Layer-Feedback-Transformers (LFT)
Check out our article here: https://huggingface.co/blog/Banaxi-Tech/layer-feedback-transformer-lft

31 replies

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posted an update 23 days ago

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Hi everyone!
We've seen some people getting confused with the BananaMind Leaderboards so ill explain!

We have 2 leaderboards, THESE are NOT the same, first BananaMind/BananaMindBench-Leaderboard which is ONLY for BananaMind Base Bench 1.1. The 10/10 scores do NOT mean that the benchmark is saturated. It isnt saturated, these models score 10/10 because they are the current best models, our /10 ranking system works by taking the ELO scores and then comparing them to the scores in the same size range. So if a better model releases that gets 10/10 and the others get lower.

And we also have the BananaMind SLM leaderboard, not the BananaMindBench leaderboard which uses ARC EASY,PIQA,Hellaswag, Arithmark 3 and the BananaMind Base Bench 1.1. This is the newer and recommended version.

Hope you understand it now!

cODeQ

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posted an update 24 days ago

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What is a model?
What is it?
You don't know?