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Banaxi-Tech  updated a Space about 6 hours ago
klein-ml/README
Banaxi-Tech  new activity 1 day ago
klein-ml/Klein-TTS-Pro-Distill-50K:hmmmm
ArushCodes  new activity 1 day ago
klein-ml/Klein-TTS-Pro-Distill-50K:hmmmm
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Banaxi-Tech 
posted an update about 6 hours ago
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635
Hi everyone
We at
saicr have found a very interesting "thing" we call ADN via interpretabillity. It appears on EVERY prompt sent to the model. More on that later.
Also I made a X account follow it for more updates:
@banaxitech

And KleinML:
@kleinmlai

Here's my website for Klein ML: https://kleinml.com/?ref=huggingface.co
Banaxi-Tech 
updated a Space about 6 hours ago
Banaxi-Tech 
in klein-ml/Klein-TTS-Pro-Distill-50K 1 day ago

hmmmm

6
#1 opened 2 days ago by
Bc-AI
ArushCodes 
in klein-ml/Klein-TTS-Pro-Distill-50K 1 day ago

hmmmm

6
#1 opened 2 days ago by
Bc-AI
Bc-AI 
in klein-ml/Klein-TTS-Pro-Distill-50K 1 day ago

hmmmm

6
#1 opened 2 days ago by
Bc-AI
Banaxi-Tech 
updated a model 2 days ago
Banaxi-Tech 
updated a dataset 2 days ago
Banaxi-Tech 
published a dataset 2 days ago
Banaxi-Tech 
published a model 2 days ago
Banaxi-Tech 
posted an update 3 days ago
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bci is the future.


and i dont like that
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Banaxi-Tech 
posted an update 4 days ago
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hi everyone
we at
klein-ml are announcing KleinMem

These models will have Native memory, without any system-prompt or prompt, it still remembers exactly.

Get early access at https://tinyurl.com/klein-eap limited to 15 users.


Architecture details are coming soon toon.

If you know alot about architecture and want to help build it, join
klein-ml .
Banaxi-Tech 
posted an update 5 days ago
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KV1 updates:

We at
klein-ml have finished stage 1 of KV1 1.2B, we don't think we will need additional stages.

KV1 2.6B is near the midpoint of training, going well so far, its going to be our most agentic model yet.

We have released Klein Code Bench klein-ml/klein-code-bench, a benchmark testing whether models can build complete projects from scratch. It contains a easy, intermediate, hard and max subset.


Here are some benchmarks of the current KV1 1.2B


It retains 75.8% of FP16 intelligence.



We are also announcing that we at
klein-ml are working on Klein 24B A2B which will be our first model featuring ternary weight quantization.
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Banaxi-Tech 
posted an update 6 days ago
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We're announcing KV1. Now.

We're going to take some models, do a bit of continued training on them and QAT them for only a 2 bit KV cache.
And because of what happened with BGA, and this is also kind of some research stuff, here's what we're going to change:
We're going to always, before we release how and make any claims, release our results.
We also would like (idk if we can) to have some external reviewers before releasing them, I'M talking to YOU @AtAndDev and @mithulaartigala
And we're going to properly cite other research.

The models we are going to release is:
KV1 1.2B, based on LFM 2.5 1.2B Instruct
KV1 2.6B, based on LFM 2.5 2.6B Instruct
KV1 4B, based on Qwen3.5 4B.

If we get enough compute, we may also train:
KV1 9B

And if you guys want to a ~27B model, you guys decide which, either on LFM 2.5 24B A2B, Qwen3.8 27B, or Qwen3.6 35B A3B.

Our goal is to get 2 bit, at 4 bit quality.

Here's an image of our current progress, KV1 is at 3 bit, not 4 bit, but it will improve!
  • 43 replies
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Banaxi-Tech 
posted an update 8 days ago
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Should I even continue making models?
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Banaxi-Tech 
posted an update 9 days ago
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Hi everyone, we're back!

And we're releasing something major again now, if you have seen Grok Bot, its very powerful, but there isn't really a local alternative yet.

Today we're releasing Minds, they're personal AI bots that live on your computer.
They can run anywhere, on your phone, on your mac, on windows, and even on linux.

They support OpenAI Oauth as the main integration because most people already have a ChatGPT sub.

But locally, It supports ANY openai compatible api which allows you to setup ollama and llama.cpp and everything else.

It uses Jev for command approval on OpenRouter and Muse Spark Transcribe for transcription.


Its fully Open Source!

Check it out: https://github.com/BananaMind/Minds
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Hoglet-33 
posted an update 10 days ago
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A few questions for everyone:

1. Should I release all Pebble 1.5 models together in one big launch, or release each model individually as it's ready?
2. What would you like to see from the Pebble models? Any specific features, capabilities, or improvements?
3. What would you like to see from basically AI as a company in general?

I'd love to hear your thoughts and suggestions!
  • 8 replies
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Banaxi-Tech 
posted an update 10 days ago
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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 😟)


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Banaxi-Tech 
posted an update 11 days ago
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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!!!!

  • 13 replies
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Banaxi-Tech 
posted an update 12 days 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!
Banaxi-Tech 
posted an update 13 days ago
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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
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