update doc

This commit is contained in:
2026-06-03 17:00:43 -04:00
parent df86299be5
commit 97322b9554

View File

@@ -180,6 +180,17 @@ qc-cli ai-hub download [--model-id ID] [--output PATH]
`ai-hub upload` runs the four Workbench upload steps in order: quantize, compile, validate, and profile. Use `--from-step compile`, `--from-step validate`, or `--from-step profile` to resume from saved local state after a completed earlier step.
Resume behavior:
```text
--from-step quantize Run quantize, compile, validate, and profile.
--from-step compile Skip quantize; compile the last quantized model unless an explicit source is passed.
--from-step validate Skip quantize and compile; validate the last compiled model.
--from-step profile Skip quantize, compile, and validate; profile the last compiled model.
```
When a step runs in the current command, `upload` passes its returned model ID directly to the next step. When a step is skipped, the next step resolves the needed model ID from `.qc-cli.json`. This avoids re-running earlier AI Hub jobs when you only need to continue from a later step.
`ai-hub compile` resolves model sources in this order: `--model-id`, explicit source options (`--onnx-path`, `--model-s3-uri`, `--from-job`), last quantized model from state, then the last training job from local state. `ai-hub download` is separate because downloading the optimized artifact is outside the four-step Workbench upload loop.
AI Hub authentication currently uses the local `qai-hub` SDK configuration. A planned follow-up is to support AWS Systems Manager Parameter Store `SecureString` for team-managed tokens, where `config.yaml` stores only a parameter name such as `/qc-cli/aihub/token`, AWS KMS encrypts the token at rest, and the CLI retrieves it at runtime with `ssm:GetParameter` plus `kms:Decrypt` permissions.