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Banaxi-Tech updated a model 4 days ago

Banaxi-Tech published a model 4 days ago

Banaxi-Tech updated a model 5 days ago

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posted an update about 11 hours ago

Post

1240

Well GPT X3 takes the lead. As of right now.

We are now announcing BananaMind 3 🍌! (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 😟)

6 replies

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posted an update 1 day ago

Post

2338

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!!!!

8 replies

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posted an update 3 days ago

Post

124

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!

posted an update 4 days ago

Post

80

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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updated a model 4 days ago

saicr/ACR-1.0

Text Generation • 57.1M • Updated 4 days ago • 50 • 3

published a model 4 days ago

saicr/ACR-1.0

Text Generation • 57.1M • Updated 4 days ago • 50 • 3

posted an update 5 days ago

Post

162

Its SAICR time tomorrow.
Get ready!

28 replies

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updated a model 5 days ago

saicr/licenses

Updated 5 days ago • 5

posted an update 6 days ago

Post

3059

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 9 days ago

Post

5160

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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updated a model 11 days ago

saicr/nacr-v1.1b

Updated 10 days ago

published a model 11 days ago

saicr/nacr-v1.1b

Updated 10 days ago

updated a model 11 days ago

saicr/nacr-v3-lite

Updated 11 days ago

published a model 11 days ago

saicr/nacr-v3-lite

Updated 11 days ago

updated a model 12 days ago

saicr/nacr-v3-lite

Updated 11 days ago

posted an update 13 days ago

Post

7615

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.

11 replies

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posted an update 15 days ago

Post

4869

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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in saicr/nacr 16 days ago

no fine-tuning?

#1 opened 16 days ago by

posted an update 16 days ago

Post

1900

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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published a model 16 days ago

saicr/nacr

Text Generation • Updated 16 days ago • 69 • 9