window.ai.finetune enables web applications to fine-tune nano/ any local AI models directly in the browser. This API allows developers to customize AI models based on specific datasets or raw text, enhancing the capabilities of client-side AI applications.
Use Cases:
Personalized language models for improved autocomplete or text generation
Custom classifiers for specific domains or user preferences
Tailored sentiment analysis models for particular contexts or industries
API:window.ai.finetune(options: FineTuneOptions)
Initiates the fine-tuning process for a model based on the provided options.
options.model: Specifies the base model to fine-tune. defaults to "nano".
options.dataset: An optional structured dataset for fine-tuning.
options.rawText: An optional string of raw text for fine-tuning.
options.epochs: An optional number of training epochs (default may vary by implementation).
options.learningRate: An optional learning rate for the fine-tuning process.
Returns a Promise that resolves to a FineTuneResult object containing the ID of the fine-tuned model and performance metrics.
window.ai.finetuneenables web applications to fine-tune nano/ any local AI models directly in the browser. This API allows developers to customize AI models based on specific datasets or raw text, enhancing the capabilities of client-side AI applications.Use Cases:
API:
window.ai.finetune(options: FineTuneOptions)Initiates the fine-tuning process for a model based on the provided options.
options.model: Specifies the base model to fine-tune. defaults to "nano".options.dataset: An optional structured dataset for fine-tuning.options.rawText: An optional string of raw text for fine-tuning.options.epochs: An optional number of training epochs (default may vary by implementation).options.learningRate: An optional learning rate for the fine-tuning process.Returns a Promise that resolves to a
FineTuneResultobject containing the ID of the fine-tuned model and performance metrics.