T5 (Text-to-Text Transfer Transformer) LLM
(Redirected from T5 (Text-to-Text Transfer Transformer))
Jump to navigation
Jump to search
A T5 (Text-to-Text Transfer Transformer) LLM is a encoder-decoder architecture large language model.
- Context:
- It can (typically) perform various natural language processing tasks by treating every task as a text generation problem, where the input and output are always strings of text.
- It can (typically) be pre-trained on a large corpus using a denoising objective, where certain spans of text are replaced with a sentinel token, and the model is trained to predict the masked span.
- It can (often) be fine-tuned on specific tasks, adapting its pre-trained knowledge to specific NLP tasks such as translation, question answering, or text summarization.
- It can demonstrate strong performance across a wide array of NLP benchmarks, showcasing its versatility and efficiency in handling different types of language tasks.
- It can (often) be available in various sizes, offering flexibility in terms of computational resources and performance needs.
- It can (typically) use a unified approach for different NLP tasks, simplifying the process of developing NLP applications by using a single model for multiple tasks.
- ...
- Example(s):
- MT5 LLM?
- ...
- Counter-Example(s):
- See: Natural Language Understanding, Text Generation, NLP Task Transformation, Transformer Models.
_