Fine-tuning
What is Fine-tuning?
Fine-tuning customizes general-purpose AI models for specific applications by training them on domain-specific data. In AI automation, this process allows organizations to leverage powerful pre-trained models while adapting them to their unique needs.
Fine-tuning enables users to create more specialized and accurate automation workflows by adapting existing models to their specific business contexts and requirements.
Why is Fine-tuning important?
Fine-tuning makes it possible to create specialized AI solutions without the enormous resources required to train models from scratch. For businesses using Lleverage, this means they can quickly develop highly accurate, domain-specific automation solutions while leveraging the power of advanced pre-trained models. This approach significantly reduces development time and resource requirements while improving accuracy for specific use cases.
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How you can use Fine-tuning with Lleverage
A legal firm uses Lleverage to automate contract analysis. They fine-tune a pre-trained language model using their historical contract database, creating a specialized model that better understands legal terminology and their specific contract formats. This results in more accurate and relevant automation for their specific needs.
Fine-tuning FAQs
Everything you want to know about
Fine-tuning
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Fine-tuning modifies the model itself through additional training, while prompt engineering involves crafting better inputs to get desired outputs from an unchanged model.
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