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alephllm-chat

Running on Zero

fix hf-mount init failure: drop models: pre-mount (training repo is large and growing; app pulls only what it needs at runtime)

e8b14b9 verified about 17 hours ago

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metadata

title: Beatrix — AlephLLM Chat
emoji: 🐠
colorFrom: yellow
colorTo: yellow
sdk: gradio
sdk_version: 6.23.1
python_version: '3.12'
app_file: app.py
pinned: false
license: mit
short_description: Talk to Beatrix — a live byte-level AlephLLM training run

Beatrix — AlephLLM chat

A live window onto the AlephLLM training runs: this space always serves the newest checkpoint of mini-beatrix-1 (112.5M params, byte-level, currently pretraining) straight from the training repo.

Completion tab — raw next-byte continuation, streamed.
Chat tab — a transcript-format preview (the model has had no chat training yet; a chat-tuned stage lands after base pretraining).
Reload — pulls the latest checkpoint mid-run; Beatrix improves as the run progresses.

The model reads raw UTF-8 bytes through a trigram-composed embedding and routes through signed geometric addresses (the aleph mechanism — sinh/Σcosh dispatch, no softmax-over-choices, inhibition first-class), with expert banks and an address-based head read that are born at exactly zero and must earn their way in by gradient.

Code and training stack: github.com/AbstractEyes/alephllm