llm_layer_collector

What problem does it solve?

This Skill provides a standardized framework for integrating new HuggingFace language model architectures into the Language Pipes distributed inference system, enabling support for a wider range of models.

Core Features & Use Cases

• Modular Architecture: Defines clear interfaces for model components (embeddings, layers, heads).
• Extensibility: Guides developers through the process of adding support for new models by modifying specific files and creating new ones.
• Use Case: A developer wants to use a newly released LLM with Language Pipes. They follow the steps in this Skill to register the model's specific architecture, allowing Language Pipes to distribute its layers across multiple machines.

Quick Start

Follow the step-by-step guide to add a new model by registering its decoder layer, RMS norm, and rotary embedding, then updating dispatch cases and creating a bespoke model file.