Instructions to use Saad381/Spectra-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Saad381/Spectra-V1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Saad381/Spectra-V1") prompt = "A cyberpunk car" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add generated example (#3)
Browse files- Add generated example (df8e36266ac213db32170a0683fa0f0157f9ff2f)
- README.md +5 -0
- images/example_zkqx9zmy2.png +0 -0
README.md
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a photo of TOK lion
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license: openrail++
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---
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# SDXL LoRA DreamBooth - Saad381/Spectra-V1
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a photo of TOK lion
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license: openrail++
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widget:
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- text: A cyberpunk car
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output:
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url: images/example_zkqx9zmy2.png
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---
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# SDXL LoRA DreamBooth - Saad381/Spectra-V1
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images/example_zkqx9zmy2.png
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