void-research (VOID)

posted an update about 13 hours ago

Post

56

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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Banaxi-Tech

posted an update 1 day ago

Post

1809

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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Banaxi-Tech

in void-research/README 2 days ago

yeah

9

#1 opened 3 days ago by

Banaxi-Tech

Hoglet-33

in void-research/README 2 days ago

yeah

9

#1 opened 3 days ago by

Banaxi-Tech

posted an update 3 days ago

Post

99

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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Hoglet-33

updated a Space 4 days ago

README

🚀

1

Hoglet-33

published a Space 4 days ago

README

🚀

1

Hoglet-33

posted an update 4 days ago

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6230

Introducing VOID. A new research branch of basically AI.

VOID — Verification of Objectives, Intentions, and Deception.

We study what lies beneath the surface: objectives, intentions, and the possibility of deception in AI systems.

There isn't much to see yet.

That will change.

Follow us for updates:

@Hoglet-33

void-research

basically-ai

7 replies

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Banaxi-Tech

posted an update 6 days ago

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2751

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

12 replies

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Banaxi-Tech

posted an update 7 days ago

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14

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

Banaxi-Tech

posted an update 8 days ago

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58

Its Monday. Getting back to working on ACR 1.0.

11 replies

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Banaxi-Tech

posted an update 11 days ago

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3020

We're releasing the BananaMind SLM Leaderboard!
It offers a easier look at which models are actually good for your specific needs.
Its primary metric, Intelligence index is a composite of BananaMind Base Bench, PIQA, Hellaswag, ARC Easy and Arithmark 3.
It also allows you to see specific categories like Commonsense on a model.

Check it out at BananaMind/BananaMind-SLM-Leaderboard

2 replies

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Banaxi-Tech

posted an update 12 days ago

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5586

AGI has arrived.

Just gotta wait for the GLM distill.

29 replies

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Hoglet-33

posted an update 15 days ago

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3196

Today, we planned to release Pebble-50M and Pebble-50M-Chat to the world. Unfortunately, due to a few issues, that didn't go quite as planned.

What happened:
- Some data and benchmark results were lost or corrupted
- The models performed worse on benchmarks than our other Pebble models

Despite that, you can still find both models here:
Pebble-50M-beta: basically-experimental/Pebble-50M-beta
Pebble-50M-Chat-beta: basically-experimental/Pebble-50M-Chat-beta

There are still some interesting improvements in these models:
- Compatible with non-CUDA devices
- Vocabulary increased to 16K tokens
- Context length increased to 16K tokens

For now, there won't be any more Pebble releases for a while. We're going to take some time to experiment with other approaches and hopefully make the next generation a monumental leap over this one.

Follow for updates:
@Hoglet-33

basically-ai

basically-experimental

4 replies

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Banaxi-Tech

posted an update 16 days ago

Post

156

Checkout

saicr .
Details coming.
We're switching goals.
Join or mission.

4 replies

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Banaxi-Tech

posted an update 19 days ago

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1943

We're releasing BananaMind Arena.
Its a Huggingface space where you can test out different models and see they're rankings!
Check it out at Banaxi-Tech/BananaMind-Arena

Also please follow @CodeSoft for inspiring me to make it.

Hoglet-33

posted an update 19 days ago

Post

3443

Pebble-25M and Pebble-25M-Chat are out now!

We’re excited to release Pebble-25M and Pebble-25M-Chat!

Both models use our 3:1 Mamba2/Transformer hybrid architecture and were pretrained on 25B tokens. Pebble-25M-Chat was then further fine-tuned on an additional 250M tokens from smol-smoltalk, following the same approach used for the Pebble-10M models.

We hope you enjoy experimenting with them!

Pebble-50M is coming in a few days.

Models
Pebble-25M: basically-ai/Pebble-25M
Pebble-25M-Chat: basically-ai/Pebble-25M-Chat
Pebble-10M GGUFs

In case you missed it, our friend @ContextReq made GGUF versions of the Pebble-10M models:

https://huggingface.co/ContextReq/Pebble-10M-GGUF
https://huggingface.co/ContextReq/Pebble-10M-Chat-GGUF

Follow us if you don’t want to miss future releases and updates!

@Hoglet-33

basically-ai

basically-experimental

7 replies

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Banaxi-Tech

posted an update 20 days ago

Post

3015

We're going to release our BananaMind 2.1 models very soon!
We're also announcing 2 new models.

All of our models we will train are:
BananaMind 2.1 Flash Lite, 10M parameters with 8M in transformer and 2M in n-gram. 50B pretraining tokens.
BananaMind 2.1 Lite with 25M parameters, 5M in n-gram and 20M in transformer. 75B pretraining tokens.
BananaMind 2.1 Flash with 50M parameters, with undecided n-gram count yet. 100B pretraining tokens.
BananaMind 2.1 Pro with 145M parameters, with undecided n-gram count yet. 150-200B pretraining tokens.
BananaMind 2.1 Coder with 149M parameters with undecided n-gram count yet.
We're now announcing BananaMind 2.1 NanoCoder, a 10M parameter model focused specifically on coding and BananaMind 2.1 MiniCoder which is a 25M parameter model focused on coding.

Follow us:

BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames

bananamind-research-community

5 replies

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Banaxi-Tech

posted an update 21 days ago

Post

2898

We're excited to release BananaMind 2.1 Pico Preview!

It includes the first preview of our BananaMind 2.1 architecture!
This model gets near BananaMind 2 Micro performance at half the parameters and 37.5x less tokens!
Thats insane!

The current architectures includes about 500K parameters of the total 1.5M parameters in n-gram embeddings and the layer 2 is run twice.

It also includes XSA and the XSA refresh gate.

We're still going to improve the architecture in the final release.

Check it out at:

Follow us for more models:

BananaMind
@Banaxi-Tech
@vovaRL
@DedeProGames

3 replies

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Hoglet-33

posted an update 22 days ago

Post

3311

Pebble 10M and Pebble 10M Chat are now released!

Both models use our Mamba/Transformer 3:1 hybrid architecture and were pretrained on 25 billion tokens.

Pebble 10M Chat was additionally fine-tuned on 250 million tokens of Smol-SmolTalk to improve its conversational capabilities.

You can find them here:

- basically-ai/Pebble-10M
- basically-ai/Pebble-10M-Chat

We hope you enjoy using them. The rest of the Pebble family will be released soon.

Follow for more:
@Hoglet-33

basically-ai

32 replies

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VOID

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