In the legal domain the adoption of transformer based language models is blocked less by capability than by resources and access: training and deployment are resource intensive and large, quality tagged legal datasets are usually restricted.
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In the legal domain, training and deploying Transformer-based Language Models (TLMs) is resource-intensive, and access to large, quality-tagged legal datasets is often restricted, hindering widespread adoption.
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