Image-to-Image
Transformers
Safetensors
English
ditfuse
image-fusion
infrared-visible-fusion
multi-focus-fusion
multi-exposure-fusion
diffusion
transformer
multimodal
text-guided
Instructions to use lijiayangCS/DiTFuse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lijiayangCS/DiTFuse with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-image" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-image", model="lijiayangCS/DiTFuse")# pip install -U transformers accelerate # Load model directly from transformers import DiTFuse model = DiTFuse.from_pretrained("lijiayangCS/DiTFuse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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