Instructions to use devemrekoc/sd-tunable with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use devemrekoc/sd-tunable with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("devemrekoc/sd-tunable", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit ·
18d0824
1
Parent(s): db42d05
Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#1)
Browse files- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (56781e8f93cd8d92e8466a353d8e74e8c67ed9ed)
Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>
scheduler/scheduler_config.json
CHANGED
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@@ -4,10 +4,10 @@
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"beta_start": 0.00085,
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"num_train_timesteps": 1000,
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"trained_betas": null
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-
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}
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"beta_end": 0.012,
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"beta_schedule": "scaled_linear",
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"beta_start": 0.00085,
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+
"clip_sample": false,
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"num_train_timesteps": 1000,
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"set_alpha_to_one": false,
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"skip_prk_steps": true,
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"steps_offset": 1,
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"trained_betas": null
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}
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