Preference Tuning LLMs with Direct Preference Optimization Methods

Preference Optimization for Vision Language Models

Optimization story: Bloom inference

Probabilistic Smoothing with Ratio-Monotone Transforms for Global Optimization

Probabilistic smoothing is a standard tool for global optimization, but existing methods rely on Gaussian kernels and specific transforms, often resulting in strong hyperparameter sensitivity and limited robustness. We propose a general smoothing framework that combines flexible symmetric unimodal kernels with monot...

🚀 Accelerating LLM Inference with TGI on Intel Gaudi

Introducing Prodigy-HF: a direct integration with Hugging Face

Optimizing your LLM in production