Announcing Tinker

TinkerToy Computer invented by Daniel Hillis and Brian Silverman Today, we are launching Tinker , a flexible API for fine-tuning language models.

It empowers researchers and hackers to experiment with models by giving them control over the algorithms and data while we handle the complexity of distributed training.

Tinker advances our mission of enabling more people to do research on cutting-edge models and customize them to their needs.

Tinker lets you fine-tune a range of large and small open-weight models, including large mixture-of-experts models such as Qwen-235B-A22B.

Switching from a small model to a large one is as simple as changing a single string in your Python code.

Tinker is a managed service that runs on our internal clusters and training infrastructure.

We handle scheduling, resource allocation, and failure recovery.

This allows you to get small or large runs started immediately, without worrying about managing infrastructure.

We use LoRA so that we can share the same pool of compute between multiple training runs, lowering costs.

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