Independent publisher

MOHAMMED KAMIL

muhamedkamil

AI & ML interests

Models in Library2

Datasets in Library0

Models on Hugging Face5

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This profile connects the 2 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Text generation.

Reported licenses: cc-by-nc-4.0. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Text generation

berna-r7-v3

MOHAMMED KAMIL

libraryname: transformers pipelinetag: text-generation - language-model - berna - dna-kernel-plexus - cells - research - non-commercial 1.2B parameter language model with self-growing cell architecture. 2. Saturation S = 0.8578 (just above threshold 0.85) Comparison: GPT-2 Small (124M) achieves HellaSwag 31.4%, ARC-Easy 44.0%, PIQA 64.1%. Berna R7 v3 (1.2B) matches this at ~15x less training data. code/ Training code config/ config.json cellsruntimecurrent/ Live cells + cognitive log cellsruntimefinal/ Final cell state checkpoints/step00010200/ Final model (with wrapper) checkpoints/step00001700/ Earlier checkpoint data/tokenized/ eng.npy, math.npy, code.npy data/tokenizer/ tokenizer.json…

Open weights cc-by-nc-4.0 transformers

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Model · Text generation

berna-r8-v3

MOHAMMED KAMIL

Each cell that saturates (S >= 0.68, K6 >= 0.03): 3. Gradient hooks - zero gradients for frozen neurons Result: Bounded Forgetting - old knowledge protected while learning new.

Open weights cc-by-nc-4.0 transformers

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