Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
diffusion
distillation
flow-matching
geometric-deep-learning
research
Instructions to use AbstractPhil/sd15-flow-lune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AbstractPhil/sd15-flow-lune with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AbstractPhil/sd15-flow-lune", 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
Upload config.json with huggingface_hub
Browse files- config.json +1 -1
config.json
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"run_name": "pretrain_pose_controlnet_v7_v10_t400_600",
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"continue_from_checkpoint": false,
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"seed": 42,
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"batch_size":
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"base_lr": 2e-06,
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"shift": 2.5,
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"dropout": 0.1,
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"run_name": "pretrain_pose_controlnet_v7_v10_t400_600",
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"continue_from_checkpoint": false,
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"seed": 42,
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"batch_size": 32,
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"base_lr": 2e-06,
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"shift": 2.5,
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"dropout": 0.1,
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