cjwbw / t2i-adapter

Learning Adapters towards Controllable for Text-to-Image Diffusion Models

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Run time and cost

This model costs approximately $0.037 to run on Replicate, or 27 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 27 seconds. The predict time for this model varies significantly based on the inputs.

Readme

Official implementation of T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models.

We propose T2I-Adapter, a simple and small (~70M parameters, ~300M storage space) network that can provide extra guidance to pre-trained text-to-image models while freezing the original large text-to-image models.

T2I-Adapter aligns internal knowledge in T2I models with external control signals. We can train various adapters according to different conditions, and achieve rich control and editing effects.