Instructions to use neuralvfx/LibreFlux-SAM-ControlNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use neuralvfx/LibreFlux-SAM-ControlNet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("neuralvfx/LibreFlux-SAM-ControlNet", 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
- Draw Things
- DiffusionBee
Update transformer/config.json
Browse files- transformer/config.json +1 -1
transformer/config.json
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{
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"_class_name": "LibreFluxTransformer2DModel",
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"_diffusers_version": "0.32",
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"_name_or_path": "/path/to/transformer",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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{
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"_class_name": "LibreFluxTransformer2DModel",
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"_diffusers_version": "0.32.0",
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"_name_or_path": "/path/to/transformer",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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