Open Source Models with Hugging Face - Syllabus

• Introduction
  • Overview of open source models on Hugging Face Hub
  • Course objectives and key concepts
• Selecting Models
  • Finding and filtering models based on tasks and requirements
  • Using Hugging Face Hub for model selection
• Natural Language Processing (NLP)
  • Basic NLP tasks with transformers
  • Example code for NLP applications
• Translation and Summarization
  • Translating and summarizing text
  • Hands-on code examples
• Sentence Embeddings
  • Generating embeddings for text similarity
  • Applications in search and retrieval
• Zero-Shot Audio Classification
  • Classifying audio without fine-tuning
  • Hands-on code examples
• Automatic Speech Recognition (ASR)
  • Converting audio to text
  • ASR examples with transformers
• Text to Speech (TTS)
  • Converting text to audio
  • Hands-on examples with TTS
• Object Detection
  • Identifying objects in images
  • Hands-on examples for object detection
• Image Segmentation
  • Zero-shot image segmentation techniques
  • Examples of identifying image regions
• Image Retrieval
  • Retrieving images based on similarity
  • Hands-on code examples
• Image Captioning
  • Generating captions for images
  • Hands-on code examples
• Multimodal Visual Question Answering
  • Answering questions based on image content
  • Hands-on code examples
• Zero-Shot Image Classification
  • Classifying images without fine-tuning
  • Hands-on code examples
• Deployment
  • Deploying applications using Gradio and Hugging Face Spaces
  • Creating user-friendly interfaces and APIs
• Conclusion
  • Recap of course concepts
  • Building blocks for AI-enabled applications