Instructions to use rockerBOO/flux.1-dev-SRPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rockerBOO/flux.1-dev-SRPO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rockerBOO/flux.1-dev-SRPO", 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
Make the model register as a quantization, instead of a finetune
Browse files
README.md
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---
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base_model:
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- tencent/SRPO
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library_name: diffusers
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license: other
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license_name: tencent-hunyuan-community
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---
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base_model:
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- tencent/SRPO
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base_model_relation: quantized
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library_name: diffusers
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license: other
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license_name: tencent-hunyuan-community
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