Flan-T5 is an instruction-tuned text-to-text transformer model developed by Google Research. It is designed to follow natural language instructions to perform a wide range of NLP tasks, including text generation, summarization, question answering, translation, and classification. Flan-T5 is optimized for both research and production environments, supporting zero-shot and few-shot learning scenarios.

Features of Flan-T5:

• Instruction-following model capable of understanding natural language prompts.
• Text-to-text architecture, where all inputs and outputs are text.
• Supports a wide range of NLP tasks including generation, summarization, QA, translation, and classification.
• Available in multiple sizes (small, base, large, XL, XXL) to balance performance and resource requirements.
• Pre-trained on instruction-based datasets for improved zero-shot and few-shot performance.
• Integration through the Hugging Face Transformers library for Python.
• Supports multilingual tasks and can generalize across different domains.
• Open-source model with flexibility for research, experimentation, and deployment.

To Check the Version of Flan-T5 and Libraries:
$ source /opt/flant5-env/bin/activate
$ python3 -c "import transformers; print(transformers.__version__)"
$ python3 -c "import torch; print(torch.__version__)"

Disclaimer: Flan-T5 is an open-source model distributed under the Apache 2.0 License. It is not affiliated with, endorsed by, or sponsored by any company other than its creators. Flan-T5 is provided "as is," without any warranty, express or implied. Users utilize this model at their own risk. Developers and contributors are not responsible for any damages