Banaxi-Tech/Deepseek-V4-Reasoning-Code-2500
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Banaxi PRO
Banaxi-Tech
AI & ML interests
SLMs, training from scratch, LoRA, TTS, Ternary models. AI Interpretability. BCI. Contact at banaxitech@gmail.com
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repliedto their post about 3 hours ago
We're releasing BananaMind 2.1 Unified, a 35M three-tower relay model where the two output towers can only talk to each other through a silent middle tower that has no output head and no loss term.
Tower B trains entirely on indirect gradient. It was never told what to predict. It woke up anyway. Jacobian lens shows it carrying the correct answer ("Paris", "oxygen", "blue") at its deepest layer. Its bridge gates grew 4-47x from init. Feed it from only one side and the representations collapse to junk — it needs both outer towers to become semantic.
The PIQA result is the cleanest demonstration: Tower A alone scores 50.11 (chance). Tower C alone 52.12. Full system 61.75. All physical reasoning lives in the integration. The 35M three-tower beats the 50M single-tower BananaMind 2 Medium on PIQA.
Trained on 38B tokens in ~7.5 hours on 8x RTX PRO 6000. Ships with 7 ablation modes so you can surgically cut the model apart without retraining. Full training logs, J-lens fits, and eval outputs for every mode included.
This is a research model. It is interesting because you can take it apart.
https://huggingface.co/BananaMind/BananaMind-2.1-Unified
Follow us for more:
https://huggingface.co/BananaMind
@Banaxi-Tech repliedto juiceb0xc0de's post about 14 hours ago
HF community! Thank you so much the overwhelming flood of downloads I've received on my model atlases over the last couple of weeks. It makes me so happy to know other people out there are enjoying my work. With that being said, I am looking for an opportunity from the builders and trainers out there.
I've recently had the chance to do a mid pre training snapshot durin process and am looking for the opportunity to get some more of these images . This is a symbiotic trade. I am more than happy to do full reports on the status of your model and translate what your model may stand to gain from as you head towards the finish line. The atlas building process uses 8965 different prompt over a wide variety of behavioural features. I combines many different methods of interpreting what is going on inside the model between prompt and response that we are unable to see.
For anyone else interested in neural network imaging and mechanistic interpretation check out my library of atlases and my new work translating the numbers into a 3d visual format to accompany the sqlite database. If you've gpt a model that you wish to have atlased leave a commen and I'kk be sure to ge arounf to it as soon as possible.
https://huggingface.co/collections/juiceb0xc0de/cloud-atlases liked a model about 14 hours ago
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