Runpod now offers access to NVIDIA’s powerful H100 GPUs, designed for generative AI workloads at scale. These next-gen GPUs deliver 7–12x performance gains over the A100, making them ideal for training massive models like GPT-4 or deploying demanding inference tasks.

Oobabooga has a 2048-token context limit, but with the Long Term Memory extension, you can store and retrieve relevant memories across conversations. This guide shows how to install the plugin, use the Character panel for persistent memory, and work around current context limitations.

Learn how to install and use Bark AI on Runpod to generate realistic, expressive synthetic voices for narration, videos, or voiceover projects—no voice cloning required.

Pygmalion 7b and Metharme 7b significantly improve on the creative writing capabilities of Pygmalion 6b. This post walks through model comparisons and how to deploy them on Runpod with the Oobabooga template.

Tired of AI gibberish in your generated images? Learn how to use DeepFloyd on Runpod to generate real English text within images, with guidance from Bill Meeks' custom notebook and tutorial.

Explore how Runpod’s persistent network volumes can save you time, money, and data headaches by allowing multi-pod access, flexible scaling, and secure, shared storage.

A performance comparison between Nvidia’s Ada and Ampere architectures, with benchmark results across Stable Diffusion and text generation workloads.