Tutorials

Learn the basics of CLIP and how to use it for zero-shot image classification.

• Loading pretrained models
• Image preprocessing
• Text prompt engineering
• Computing similarities

Create a semantic image search system using CLIP embeddings and FAISS indexing.

• Batch embedding extraction
• FAISS index construction
• Text-to-image search
• Performance optimization

Transcribe audio files and streams using OpenAI's Whisper model.

• Model selection guide
• Audio preprocessing
• Multilingual transcription
• Word-level timestamps

Build a VQA system using vision-language models like LLaVA.

• VLM architecture overview
• Image-text fusion
• Generating responses
• Evaluation metrics

Implement different fusion strategies for combining vision, text, and audio.

• Early vs late fusion
• Cross-attention mechanisms
• Gated fusion networks
• Training strategies

Optimize multimodal models for production deployment.

• ONNX export
• TensorRT optimization
• Quantization (INT8)
• Batching strategies

Adapt CLIP to domain-specific tasks through fine-tuning.

• Dataset preparation
• Contrastive loss setup
• Learning rate scheduling
• Evaluation and iteration

Build real-time multimodal inference pipelines for video and audio streams.

• Stream processing
• Async inference
• Frame batching
• Latency optimization