Instructions to use SuhZhang/CorrAdapter-Model-on-MVAdapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SuhZhang/CorrAdapter-Model-on-MVAdapter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SuhZhang/CorrAdapter-Model-on-MVAdapter", 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
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README.md
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@@ -31,7 +31,7 @@ From the CorrAdapter MVAdapter directory:
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```bash
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python -m scripts.inference_i2mv_sdxl \
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--adapter_path
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--adapter_weight_name pytorch_model.bin.index.json \
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--image assets/demo/i2mv/A_decorative_figurine_of_a_young_anime-style_girl.png \
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--text "A decorative figurine of a young anime-style girl" \
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```bash
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python -m scripts.inference_i2mv_sdxl \
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--adapter_path SuhZhang/CorrAdapter-Model-on-MVAdapter \
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--adapter_weight_name pytorch_model.bin.index.json \
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--image assets/demo/i2mv/A_decorative_figurine_of_a_young_anime-style_girl.png \
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--text "A decorative figurine of a young anime-style girl" \
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