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CMU & Tsinghua U’s Prompt2Model Generates Deployable Models Following Natural Language Instructions
In a new paper Prompt2Model: Generating Deployable Models from Natural Language Instructions, a research team from Carnegie Mellon University and Tsinghua University introduces Prompt2Model, a general-purpose approach that is able to use prompting technique to specify system behavior while resulting in a deployable special purpose model that enjoys all the advantages thereof.
The post CMU & Tsinghua U’s Prompt2Model Generates Deployable Models Following Natural Language Instructions first appeared on Synced.
ai artificial intelligence behavior carnegie mellon carnegie mellon university cmu deep-neural-networks general language large language model machine learning machine learning & data science ml natural natural language natural language processing paper prompting research research team team technology tsinghua university university