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Google FLAN T5

FLAN fine-tunes the model on a large set of varied instructions that use a simple and intuitive description of the task, such as “Classify this movie review as positive or negative,” or “Translate this sentence to Danish.”

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Google FLAN Models

Welcome to the Google FLAN family of models! These sophisticated AI models represent an improvement over the T5 models. Imagine them like your regular T5 models, but now better at handling a wider array of tasks and accommodating more languages.

FLAN models boast state-of-the-art performance and are fine-tuned for over 1000 tasks, demonstrating strong results, especially in few-shot performances. This advancement translates to improved performance in applications like reasoning and question-answering.

Part of the charm also lies in the model’s broad language support, covering a vast list from English, Spanish, and Japanese to less commonly supported languages such as Lao, Yoruba, or Oriya, among many others.

The FLAN models are designed predominantly for research purposes, particularly in language model studies, fairness and safety research, and understanding current large language model limitations. However, they can still be employed in real-world applications given appropriate fine-tuning and considerations.

Remember, these models are licensed under Apache 2.0, and links to their original checkpoints are provided for reference. For a more detailed idea of their workings, structure, and performance, you may want to visit the Research Paper or the GitHub Repo .

Bear in mind that as powerful as these models are, they should always be used responsibly considering their inherent biases and limitations.

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