GitHub - ritabratamaiti/AnyModal: AnyModal is a Flexible Multimodal Language Model Framework

AnyModal is a flexible, modular, and extensible framework designed to integrate various input modalities such as images and audio into large language models (LLMs). It allows easy tokenization, encoding, and language generation using pre-trained models for different modalities. Key features include flexible integration of different input modalities, tokenization support for non-text modalities, and an extensible design that allows for the addition of new input processors and tokenizers with minimal code changes.

To use AnyModal, users are advised to read through the provided steps and examples in the 'demos' directory. The process involves installation and setup, implementing input modality tokenization, training and inference, and extending AnyModal by implementing new input processors and tokenizers. The project is open for contributions, and users are encouraged to join the subreddit r/AnyModal to discuss ideas, ask questions, and share their projects. The project is licensed under the MIT License.

Key takeaways:

AnyModal is a flexible and extensible framework for integrating diverse input modalities into large language models.
Key features of AnyModal include flexible integration, tokenization support, and an extensible design that allows for easy addition of new input processors and tokenizers.
AnyModal requires three core components for input processing: an input processor, an input encoder, and an input tokenizer.
Contributions to AnyModal are welcome and can range from fixing bugs, improving documentation, or adding support for new input modalities.

GitHub - ritabratamaiti/AnyModal: AnyModal is a Flexible Multimodal Language Model Framework

Key takeaways:

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