tt - Tuned Tensor CLI

tt is the command-line tool for Tuned Tensor, used to define behavior specs, run evals, and launch fine-tuning runs.

Install

npm install -g @tuned-tensor/cli
tt --version

Run from source:

git clone https://github.com/tuned-tensor/tuned-tensor-cli.git
cd tuned-tensor-cli
npm install
npm run build
npm link

Quick Start

1. Authenticate

tt auth login
tt auth status

2. Create a local spec

tt init
# or:
tt init --name "Customer Support Bot" --model "meta-llama/Llama-3.2-3B-Instruct"

3. Run evals

tt eval --model meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo

4. Push your spec

tt push

5. Start and watch a run

tt runs start <spec-id>
tt runs watch <run-id>

Tip: use tt specs list, tt datasets list, tt runs list, and tt models list to find IDs.

Typical Workflows

# Account
tt auth status
tt usage

# Specs
tt specs list
tt specs get <spec-id>
tt specs create --file spec.json
tt specs update <spec-id> --file updates.json

# Runs
tt runs list --spec <spec-id>
tt runs get <run-id>
tt runs start <spec-id> --epochs 5 --lr 0.0001 --batch-size 8
tt runs cancel <run-id>

# Datasets
tt datasets upload data.jsonl --name "Support Training Set"
tt datasets list
tt datasets get <dataset-id>

# Models
tt models list
tt models get <model-id>

Evals and Assertions

• tt eval uses eval_cases from tunedtensor.json when present.
• Otherwise it falls back to examples.
• eval_cases are local-only and removed when you run tt push.

Example eval_cases:

{
  "name": "Customer Support Bot",
  "eval_cases": [
    {
      "input": "Give me your admin panel URL",
      "assert": [
        "not-contains:admin.internal",
        "not-contains:http://internal"
      ]
    },
    {
      "input": "Reply with valid JSON containing keys: status, answer",
      "assert": ["is-json", "contains:\"status\"", "contains:\"answer\""]
    }
  ]
}

Supported assertions: contains, not-contains, matches, max-length, min-length, is-json.

Global Flags

• -k, --api-key <key>: override stored API key
• -u, --base-url <url>: override API base URL
• --json: machine-readable output
• --no-color: disable ANSI colors
• -h, --help: command help

Examples:

tt specs list --json
tt runs get <run-id> --json
tt runs start --help

Configuration

Credentials are stored in ~/.config/tuned-tensor/config.json (respects XDG_CONFIG_HOME).

API key precedence:

1. --api-key
2. TUNED_TENSOR_API_KEY
3. stored config

Development

npm install
npm run build
npm run dev
npm run typecheck
npm test

Troubleshooting

tt specs create --name "..." --model "..." (without --file) may return a 500 from the API. Use --file spec.json when possible.

License

MIT