How to use
ModelScope.

1. 01

   Start at https://modelscope.cn/ and confirm the domain before entering account or payment information.

2. 02

   Availability: ModelScope is available through its web hub plus the modelscope and modelscope-hub Python packages and ms-hub command-line interface.

3. 03

   Python 3.10 or later for the current hub client, sufficient local or cloud compute and storage, a ModelScope token for private or publishing operations, verified asset licenses and revisions, and a sandboxed evaluation environment.

4. 04

   Sign in with the account you intend to keep using, then review plan, data, notification, and permission settings.

5. 05

   Run one low-risk test task before connecting sensitive files, repositories, or workspace data.

• Use official download pages.
• Review permissions during setup.
• Keep installers and applications updated.

1. 01

   Define the task, modalities, model and dataset rights, quality, safety, hardware, storage, code-trust, privacy, provenance, deployment, and reproducibility requirements.

2. 02

   Shortlist repositories by model card, license, owner, revision, files, dependencies, task fit, evaluation evidence, and whether loading requires remote or custom code.

3. 03

   Download a pinned revision into an isolated environment, verify hashes and files, scan dependencies and serialized artifacts, and run a frozen representative benchmark without sensitive data.

4. 04

   Record the selected revision, license, environment, quality and safety results, limitations, and lineage, then publish or deploy only through scoped credentials and a reviewed rollback plan.

• State the outcome before the background.
• Provide the real source material.
• Review the result before expanding the task.

1. 01

   Restate the intended behaviour and the acceptance criteria before reading a single generated line.

2. 02

   Read the diff rather than the chat summary; the summary describes intent, the diff describes what actually changed.

3. 03

   Run the test suite, then write a test that would fail if the change were wrong, and confirm it passes for the right reason.

4. 04

   Check the edges the model tends to skip: error paths, null and empty cases, concurrency, and migration or rollback behaviour.

5. 05

   Trace every new dependency, network call, and file write, and confirm each one is genuinely required.

• Review the diff, never the description of the diff.
• A passing test suite proves the tests pass, not that the change is correct.
• Keep changes small enough that a human can actually review them.

1. 01

   Decide what the tool may read and what it may write before connecting a repository.

2. 02

   Scope tokens and integrations to the narrowest repository, branch, and permission set that still works.

3. 03

   Keep secrets out of the context window: use environment variables and secret stores, never inline credentials.

4. 04

   Require review before generated code touches authentication, payments, permissions, migrations, or deletion paths.

5. 05

   Audit what the integration retained after the session, and revoke access that is no longer needed.

• A hub listing is not an independent security, quality, or licensing review. Model repositories, datasets, notebooks, serialized weights, dependencies, Studio apps, MCP servers, and custom loading code can execute code or expose data. Pin revisions, inspect cards and licenses, verify hashes, isolate execution, avoid secrets and sensitive data, limit tokens, and preserve provenance and deletion controls.
• Follow your organisation's approved-use policy.
• Never treat fluent output as authorization to act.

• ModelScope Hub client ↗
• ModelScope framework ↗
• ModelScope Skills hub guide ↗
• ModelScope platform ↗

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