1 रिपॉजिटरी
Generation of programming code sequences token-by-token by feeding previous outputs back into the model decoder.
Distinct from Autoregressive Text Generation: Specifically targets source code modality rather than general natural language text.
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CodeGen is a trained large language model and program synthesis model designed to generate functional source code. It utilizes a neural network architecture to synthesize executable code from natural language descriptions or partial code snippets. The model enables automated program synthesis and AI-assisted coding by predicting and filling in missing sections of code within a program. It transforms natural language descriptions into functional programming logic to automate the creation of boilerplate and logic.
Implements an autoregressive mechanism to produce source code incrementally by predicting the next token based on previous context.