Instructions to use ccc8/c7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ccc8/c7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ccc8/c7", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece forest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update unet/config.json
Browse files- unet/config.json +1 -1
unet/config.json
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"resnet_out_scale_factor": 1.0,
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"resnet_skip_time_act": false,
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"resnet_time_scale_shift": "default",
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"sample_size":
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"time_cond_proj_dim": null,
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"time_embedding_act_fn": null,
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"time_embedding_dim": null,
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"resnet_out_scale_factor": 1.0,
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"resnet_skip_time_act": false,
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"resnet_time_scale_shift": "default",
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"sample_size": 256,
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"time_cond_proj_dim": null,
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"time_embedding_act_fn": null,
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"time_embedding_dim": null,
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