#Transformers

Explore the differences between Transformers and MoE models regarding performance and architecture.

'A practical tutorial on building a fully offline multi-tool reasoning agent using Instructor, Transformers and Pydantic. Includes code for tool mocks, schemas, routing and recovery.'

Explore how to build local multi-endpoint ML APIs with LitServe, showcasing batching, streaming, caching and multi-task inference with Hugging Face pipelines.

Meta AI's Token-Shuffle method reduces the number of image tokens in Transformer models, allowing efficient high-resolution image synthesis with improved quality and lower computational cost.