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# Models on Hugging Face
# Models on Hugging Face
Hugging Face offers a wide range of models for generating embeddings across various modalities. Text embeddings convert sentences or documents into vectors for tasks like semantic similarity and information retrieval. Image embeddings represent visual data for classification or similarity detection, while multimodal embeddings handle combined inputs like text and images. Audio embeddings process speech and sounds, and code embeddings facilitate understanding and searching code snippets. These models power many modern AI applications, from chatbots to recommendation systems.

Learn more from following resources:
- [@article@Get started with Hugging Embeddings](https://huggingface.co/blog/getting-started-with-embeddings)