riton-inference-server/backend: Common source, scripts and utilities for creating Triton backends.

Common source, scripts and utilities for creating Triton backends.

Triton Inference Server Backend A Triton backend is the implementation that executes a model. A backend can be a wrapper around a deep-learning framework, like PyTorch, TensorFlow, TensorRT or ONNX Runtime. Or a backend can be custom C/C++ logic performing any operation (for example, image pre-processing). This repo contains documentation on Triton backends and also source, scripts and utilities for creating Triton backends. You do not need to use anything provided in this repo to create a Triton backend but you will likely find its contents useful. Frequently Asked Questions Full documentatio

related reading

• server/docs/user_guide/model_configuration.md at main · triton-inference-server/server · GitHubgithub.com
• tutorials/Conceptual_Guide/Part_1-model_deployment at main · triton-inference-server/tutorials · GitHubgithub.com
• tutorials/Conceptual_Guide/Part_4-inference_acceleration/README.md at main · triton-inference-server/tutorials · GitHubgithub.com
• tutorials/HuggingFace at main · triton-inference-server/tutorials · GitHubgithub.com
• Inkling: Our Open-Weights Model - Thinking Machines Labthinkingmachines.ai
• API Reference — TensorRT LLMnvidia.github.io
• Inference Platform: Deploy AI models in production | Basetenbaseten.co
• LLM Inference Performance Engineering: Best Practices | Databricks Blogdatabricks.com
• GitHub - triton-lang/triton: Development repository for the Triton language and compiler · GitHubgithub.com
• frontier model training methodologies | Alex Wa's Blogdjdumpling.github.io
• Interpretability Infrastructure at Frontier Scale: Harvesting Activations from a Trillion-Parameter Modelgoodfire.ai
• Transformer Math 101 | EleutherAI Blogblog.eleuther.ai