Instructions to use BiliSakura/MVSplit-DiT-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/MVSplit-DiT-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/MVSplit-DiT-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "a red panda climbing a bamboo stalk" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Delete model_index.json
Browse files- model_index.json +0 -27
model_index.json
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{
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"_class_name": [
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"pipeline",
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"MVSplitDiTPipeline"
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],
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"_diffusers_version": "0.36.0",
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"scheduler": [
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"diffusers",
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"FlowMatchEulerDiscreteScheduler"
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],
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"transformer": [
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"transformer_mvsplit_dit",
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"MVSplitDiTTransformer2DModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKLFlux2"
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],
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"text_encoder": [
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"transformers",
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"AutoModel"
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],
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"tokenizer": [
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"transformers",
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"AutoTokenizer"
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]
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}
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