Modified on Fri, 13 Oct 2023 at 07:15 AM

FineTune is a tool that allows you to customize pre-trained models to optimize their performance using your data. FineTune is a no-code tool that takes an existing foundation model or any other kind of pre-trained model and tunes it on new data without training the model from scratch. FineTune enables you to seamlessly create more accurate models with less training time.

How to use FineTune?

You can use FineTune for various functions, such as translation, speech recognition, text summarization, etc. You can also use FineTune with aiXplain's other tools, such as Discover, Benchmark, AutoMode, and Design. 

To use FineTune, you need to follow these steps:

  1. Model Selection: Choose the model you wish to FineTune. Select from models available on the aiXplain marketplace or upload your own. Refine your choices based on price and popularity considerations.
  2. Data Input: Opt for data for fine-tuning. You can upload your datasets or utilize existing ones from Discover. Easily partition your data into training, validation, and test sets using sliders or manual configuration.
  3. Training the Model: Initiate the training process for your FineTune model. Monitor its progress, run the job, and access fine-tune logs. Benchmark reports are also available to gauge performance.
  4. Integration and Use: Put your FineTune model to work synchronously or asynchronously using aiXplain's SDK or API. Seamlessly incorporate the FineTune model into your existing pipeline with the Design tool.

What are the benefits of FineTune?

  • Model Customization: Tailor pre-trained models to suit your unique task or domain using your own data.

  • Enhanced Performance: Elevate the accuracy and quality of your models by fine-tuning them on relevant datasets.

  • Time and Resource Efficiency: Reduce model training time and cost by leveraging transfer learning instead of starting from scratch.

  • Effortless Data Partitioning: Seamlessly divide your data into training, validation, and test sets using sliders or manual configuration.

I hope this article has proven to be both helpful and informative for you. We greatly appreciate your decision to select aiXplain as your AI creation and optimization partner. Should you have any inquiries or feedback, please don't hesitate to reach out to us at your convenience.

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