Instructions to use lohpaul/SketchyBusinessControlNet_image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lohpaul/SketchyBusinessControlNet_image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lohpaul/SketchyBusinessControlNet_image", 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
Upload model
Browse files- config.json +1 -1
- diffusion_pytorch_model.safetensors +1 -1
config.json
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{
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"_class_name": "ControlNetModel",
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"_diffusers_version": "0.32.0.dev0",
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"_name_or_path": "
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"act_fn": "silu",
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"addition_embed_type": null,
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"addition_embed_type_num_heads": 64,
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{
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"_class_name": "ControlNetModel",
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"_diffusers_version": "0.32.0.dev0",
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"_name_or_path": "output_model_last_completed/controlnet_image",
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"act_fn": "silu",
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"addition_embed_type": null,
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"addition_embed_type_num_heads": 64,
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1445157120
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version https://git-lfs.github.com/spec/v1
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oid sha256:6939732a05286374140eabb855a4d614ceab0857dd62699da5ffb7320e5dfece
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size 1445157120
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