Core MLApple
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TinkerThinking Machines Lab
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Related Products
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About
Core ML applies a machine learning algorithm to a set of training data to create a model. You use a model to make predictions based on new input data. Models can accomplish a wide variety of tasks that would be difficult or impractical to write in code. For example, you can train a model to categorize photos or detect specific objects within a photo directly from its pixels. After you create the model, integrate it in your app and deploy it on the user’s device. Your app uses Core ML APIs and user data to make predictions and to train or fine-tune the model. You can build and train a model with the Create ML app bundled with Xcode. Models trained using Create ML are in the Core ML model format and are ready to use in your app. Alternatively, you can use a wide variety of other machine learning libraries and then use Core ML Tools to convert the model into the Core ML format. Once a model is on a user’s device, you can use Core ML to retrain or fine-tune it on-device.
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About
Tinker is a training API designed for researchers and developers that allows full control over model fine-tuning while abstracting away the infrastructure complexity. It supports primitives and enables users to build custom training loops, supervision logic, and reinforcement learning flows. It currently supports LoRA fine-tuning on open-weight models across both LLama and Qwen families, ranging from small models to large mixture-of-experts architectures. Users write Python code to handle data, loss functions, and algorithmic logic; Tinker handles scheduling, resource allocation, distributed training, and failure recovery behind the scenes. The service lets users download model weights at different checkpoints and doesn’t force them to manage the compute environment. Tinker is delivered as a managed offering; training jobs run on Thinking Machines’ internal GPU infrastructure, freeing users from cluster orchestration.
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Platforms Supported
Windows
Not Supported
Mac
Supported
Linux
Not Supported
Cloud
Not Supported
On-Premises
Not Supported
iPhone
Supported
iPad
Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Developers in search of a solution to integrate machine learning models into their apps
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Audience
AI researchers and ML engineers requiring a solution to experiment with fine-tuning open source language models while outsourcing infrastructure complexity
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationApple
United States
developer.apple.com/documentation/coreml
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Company InformationThinking Machines Lab
United States
thinkingmachines.ai/tinker/
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
Apple tvOS
Supported
Apple watchOS
Supported
Inkling
Not Supported
Inkling-Small
Not Supported
Llama 3
Not Supported
Llama 3.1
Not Supported
Llama 3.2
Not Supported
Llama 3.3
Not Supported
Python
Not Supported
Qwen
Not Supported
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Integrations
Apple tvOS
Not Supported
Apple watchOS
Not Supported
Inkling
Supported
Inkling-Small
Supported
Llama 3
Supported
Llama 3.1
Supported
Llama 3.2
Supported
Llama 3.3
Supported
Python
Supported
Qwen
Supported
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