Instructions to use harsha19/ramya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use harsha19/ramya with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("harsha19/ramya") prompt = "rups" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update config (1).yaml
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config (1).yaml
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sample:
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sampler: flowmatch
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sample_every: 1000
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width:
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height: 1024
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prompts:
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- A person in a bustling cafe anas
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sample:
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sampler: flowmatch
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sample_every: 1000
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width: 800
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height: 1024
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prompts:
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- A person in a bustling cafe anas
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