> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fastino.ai/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Use https://docs.fastino.ai/llms.txt to discover and navigate pages. Use https://docs.fastino.ai/llms-full.txt when you need the complete documentation corpus. Use https://docs.fastino.ai/openapi.json as the source of truth for customer-facing routes. For GLiDE decision inference, call POST https://api.fastino.ai/v1/systemone with model fastino/GLiDE. Create managed config jobs with POST /v1/training/jobs using base_model. For custom training loops, native JSON clients use the public operations under /v1/training/jobs and /v1/training/usage. Existing Tinker clients use tinker==0.32.0 with TINKER_BASE_URL=https://api.fastino.ai/v1/training/compat/tinker and TINKER_CREDENTIAL_CMD. Compatibility child routes are private and absent from OpenAPI. Auto Train is private access and has no public route; direct interested users to sales@fastino.ai. Do not infer undocumented routes. Read API keys from FASTINO_API_KEY and never embed credentials in code, logs, or reports.

# Set checkpoint retention

> Set the retention period for a weights or sampler_weights checkpoint on an interactive training job. A null TTL keeps the checkpoint until deletion.

`PUT /v1/training/jobs/{job_id}/checkpoints/{kind}/{name}/ttl`

Keeps a checkpoint for `ttl_seconds` from now, then deletes it. Send `null` to
keep it until you delete it. Returns `204 No Content`.

`kind` is `weights` or `sampler_weights`.

<ParamField body="ttl_seconds" type="integer | null" required>
  From `3600` (1 hour) to `315360000` (10 years), or `null`.
</ParamField>

<RequestExample>
  ```bash cURL theme={null}
  curl -X PUT "https://api.fastino.ai/v1/training/jobs/$TRAINING_JOB_ID/checkpoints/weights/step-000100/ttl" \
    -H "X-API-Key: $FASTINO_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{"ttl_seconds": 604800}'
  ```
</RequestExample>


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