Train a model
Use the training client to compute gradients and perform optimizer steps for your training workflow.
Build model training and sampling workflows with Thinking Machines’ Tinker API and Python SDK.
Use the training client to compute gradients and perform optimizer steps for your training workflow.
Use a sampling client to generate text from a model or trained checkpoint.
Operation documentation reviewed . These are starting workflows, not a complete capability list or a runtime test.
Build model training and sampling workflows with Thinking Machines’ Tinker API and Python SDK.
Authentication and permission requirements have not been reviewed here. Check the provider documentation for the required keys, OAuth scopes and account access before sending a request.
Check provider documentation ↗Account-free API calls have not been verified for this profile. You can inspect specifications and prepare requests in the explorer without running them.
Requests run only when you choose to send them. Browser access depends on the provider’s CORS policy.
This profile contains a reviewed summary. Pricing, rate limits, authentication requirements, and SDK availability should be checked in the provider documentation before implementation. MCP support has not been established in this curated entry.
QUICK ANSWERS
Build model training and sampling workflows with Thinking Machines’ Tinker API and Python SDK.
Use the linked Tinker (Thinking Machines) provider documentation to check setup and supported capabilities.
Read documentationAPI Tracker summarizes available catalog information. Missing fields mean we have not established those details; they do not mean a feature is unsupported. Confirm current requirements with the provider.
Read our methodologyMatched by shared capabilities or focused collections. These are options to evaluate, not verified integrations or drop-in replacements.