Instructions to use InstantX/SD3-Controlnet-Pose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/SD3-Controlnet-Pose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/SD3-Controlnet-Pose", torch_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
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README.md
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# Demo
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```python
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import torch
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from diffusers import StableDiffusion3Pipeline
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from diffusers.models.controlnet_sd3 import ControlNetSD3Model
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from diffusers.utils.torch_utils import randn_tensor
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import sys, os
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sys.path.append('/path/diffusers/examples/community')
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from pipeline_stable_diffusion_3_controlnet import StableDiffusion3CommonPipeline
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# load pipeline
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base_model = 'stabilityai/stable-diffusion-3-medium-diffusers'
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pipe = StableDiffusion3CommonPipeline.from_pretrained(
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# Demo
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```python
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import torch
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from diffusers.utils.torch_utils import randn_tensor
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import sys, os
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sys.path.append('/path/diffusers/examples/community')
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from pipeline_stable_diffusion_3_controlnet import StableDiffusion3CommonPipeline
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# load pipeline
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base_model = 'stabilityai/stable-diffusion-3-medium-diffusers'
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pipe = StableDiffusion3CommonPipeline.from_pretrained(
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