This project explores various open-source models available on Hugging Face 🤗 and demonstrates their application across diverse AI tasks. From audio 🎵 and image 🖼️ analysis to text processing 📝, the project showcases how these models can be accessed either via endpoint APIs 🌐 or by directly downloading and running them locally 💻.
Key Features:
- Audio and Image Classification 🎧🖼️: Implements models to classify audio signals and images into predefined categories.
- Image Captioning 🖼️📝: Generates descriptive captions for images using state-of-the-art image-to-text models.
- Image Retrieval 🖼️🔍: Enables retrieving similar images based on input queries or visual features.
- Object Detection 📸📦: Identifies and labels objects within an image using advanced detection models.
- Sentence Embedding 📝🔗: Converts text into dense vector representations for downstream tasks like similarity search.
- Text Summarization 📚✂️: Summarizes lengthy text into concise and coherent summaries.
Access Methods:
- Endpoint API 🌐: Accesses Hugging Face models via API endpoints for quick and efficient usage.
- Local Deployment 💻: Downloads and runs models locally for greater flexibility and control.