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Running on Zero
Running on Zero
File size: 1,308 Bytes
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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](https://huggingface.co/AbstractPhil/alephllm-mini-beatrix-training).
- **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](https://github.com/AbstractEyes/alephllm)
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