Instructions to use BiliSakura/JiT-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/JiT-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/JiT-diffusers", 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
Delete JiT-B-32/config.json
Browse files- JiT-B-32/config.json +0 -14
JiT-B-32/config.json
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{
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"_class_name": "JiTTransformer2DModel",
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"_diffusers_version": "0.36.0",
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"attention_dropout": 0.0,
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"attn_dropout": null,
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"dropout": 0.0,
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"image_size": null,
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"model_name": null,
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"model_type": "JiT-B/32",
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"num_class_embeds": 1000,
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"num_classes": null,
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"proj_dropout": null,
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"sample_size": 512
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}
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