The Transformers framework offers the following significant advantages:
- Model resourcefulness:Provides more than 1 million pre-trained models covering all types of tasks
- Multi-framework compatibility:Simultaneous support for PyTorch, TensorFlow and Flax
- Ease of use:The Pipeline API lowers the barrier to use, allowing complex functionality to be implemented in a few lines of code.
- Continuously updated:Timely integration of the latest models such as Kyutai-STT (speech), ColQwen2 (vision)
- Ecological perfection:Provides a complete ecosystem of model hosting (Hugging Face Hub), offline support, command line tools, and more!
It is especially worth mentioning that Transformers is particularly good at handling multimodal tasks, which is a shortcoming of many traditional frameworks. Its unified API design also allows users to quickly apply it to real projects without having to learn in-depth about the specific implementation of different models.
This answer comes from the articleTransformers: open source machine learning modeling framework with support for text, image and multimodal tasksThe
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