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TriChronos-0.1B setup
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A newer version of the Gradio SDK is available: 6.24.0

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metadata 
title: TriChronos Train
emoji: 🧠
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 5.34.2
python_version: '3.11'
app_file: app.py
pinned: true
hardware: a100-large
storage: small

TriChronos-0.1B — Training Space

This Space trains TriChronos-0.1B (100M-param ternary time-series forecasting model) on Salesforce/lotsa_data.

Setup checklist (one-time, manual steps on HF)

  1. Settings → Hardware → upgrade to Nvidia A100 - large (~$2.50/hr)
  2. Settings → Persistent storage → enable (so checkpoints survive restarts)
  3. Settings → Variables and Secrets → add:
    • HF_TOKEN = your HF write token
    • SPACE_ID = iravikr/trichronos-train
  4. Restart the Space — training will start automatically when the app loads.

What the UI shows

  • Live training log — streams stdout from train.py
  • Loss tracker — latest checkpoint loss from checkpoints/loss.txt
  • Budget meter — elapsed wall-clock time vs. 7h10m hard limit
  • Start / Stop buttons