Instructions to use lsmpp/kontextrefiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lsmpp/kontextrefiner with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lsmpp/kontextrefiner", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
SD3Transformer2D
This class is useful when only loading weights into a [SD3Transformer2DModel]. If you need to load weights into the text encoder or a text encoder and SD3Transformer2DModel, check SD3LoraLoaderMixin class instead.
The [SD3Transformer2DLoadersMixin] class currently only loads IP-Adapter weights, but will be used in the future to save weights and load LoRAs.
To learn more about how to load LoRA weights, see the LoRA loading guide.
SD3Transformer2DLoadersMixin
[[autodoc]] loaders.transformer_sd3.SD3Transformer2DLoadersMixin - all - _load_ip_adapter_weights