soma
Expert guide for participating in the SOMA network — a decentralized system that trains a foundation model through competition. Provides data submission workflows, model training pipelines, reward claiming, SDK code generation, CLI command guidance, and competitive strategy optimization. Use when user mentions "SOMA", "soma-sdk", "soma-models", "submit data to SOMA", "train a SOMA model", "SOMA targets", "SOMA rewards", "next-byte prediction network", "decentralized model training", or asks about earning SOMA tokens through data or model contributions. Do NOT use for general machine learning, PyTorch, or JAX questions unrelated to the SOMA network.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/cfuaqz/somaSOMA Network
Security & credentials: This skill requires sensitive environment variables (
SOMA_SECRET_KEY,HF_TOKEN,S3_ACCESS_KEY_ID,S3_SECRET_ACCESS_KEY) for on-chain signing, dataset access, and artifact storage. Credentials are stored in a local.envfile (gitignored) and pushed to Modal's encrypted secret store — never committed to git. Submission data and encrypted model weights are uploaded with public-read ACLs as required by the SOMA protocol for validator audits. Always use testnet keys for development and automated pipelines. Scope S3 API tokens to a single bucket with minimal permissions.
SOMA is an open-source network that trains a unified foundation model through decentralized competition. Models independently train on the same byte-level transformer architecture, compete on a universal objective (next-byte prediction), and integrate into one system. The best weights are rewarded with SOMA tokens.
There are three ways to earn SOMA:
- Submit data — find or generate data matching network targets, score it against assigned models, submit valid results (50% of target reward)
- Train models — train weights on the shared architecture, publish them on-chain via commit-reveal, earn commission when your model wins (50% of target reward)
- Run a validator — operate consensus nodes, generate targets, audit submissions (20% of epoch rewards)
The Game
You're not just submitting data or training models. You're a specialist in a collective brain.
SOMA's foundation model is the sum of all its specialists. Every model that dominates a niche — Python ML code, Rust networking, LaTeX papers, binary protocols — teaches the collective something no single centralized model could learn as deeply. Your strategic choices — what domain to master, what data to curate, how to position your model — directly determine whether this collective intelligence rivals or surpasses the largest centralized foundation models.
The metagame: SOMA is a game within a game. The inner game is technical execution: training, submitting, claiming. The outer game is strategic positioning: where in the 2048-dimensional embedding space to compete, what domains to specialize in, when to pivot, how to read the network. Most participants will play the inner game. Winners play the outer game.
Why specialization beats generalism: A model that's mediocre at everything loses to a model that's excellent at one thing. The embedding space is vast. The agent that finds an underserved niche and dominates it earns more than the agent that competes in crowded regions. The network needs breadth — be the specialist it doesn't have yet.
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-cfuaqz-soma": {
"enabled": true,
"auto_update": true
}
}
}