Pre-training

The initial phase of training a model on large datasets to develop foundational knowledge before fine-tuning.

What is Pre-training?

Pre-training is the process of building foundational AI capabilities through extensive initial training. In AI automation, pre-trained models provide a strong starting point for specific applications.

Pre-training helps in leveraging existing model capabilities effectively while knowing when additional training is needed.

Why is Pre-training important?

Pre-training significantly reduces the time and resources needed to develop AI solutions. For businesses using Lleverage, pre-trained models offer sophisticated capabilities out of the box, which can then be customized for specific needs. This approach makes advanced AI automation more accessible and cost-effective.

How you can use
Pre-training
with Lleverage

A legal tech company uses Lleverage to build contract analysis workflows. They leverage pre-trained language models that already understand general language patterns, then fine-tune them for legal terminology and contract structures, significantly reducing development time.

Pre-training
FAQs

Everything you want to know about

Pre-training

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How does pre-training differ from fine-tuning?

Pre-training builds general capabilities on large datasets, while fine-tuning adapts these capabilities to specific tasks.

What are the benefits of using pre-trained models?

Pre-trained models offer sophisticated capabilities without the need for extensive training resources, reducing development time and costs.

More references for
Pre-training

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