Instructions to use Xena18284/Test123 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Xena18284/Test123 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("Xena18284/Test123") prompt = "a red Nissan GTR R35 in a rainy city scene" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add generated example
#1
by Xena18284 - opened
- README.md +14 -8
- images/example_30v5f8gp9.png +3 -0
README.md
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---
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tags:
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widget:
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base_model:
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instance_prompt:
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pipeline_tag: text-to-image
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library_name: diffusers
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metrics:
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---
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# Test123
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tags:
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- text-to-image
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- lora
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- diffusers
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- flux-diffusion
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widget:
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- text: a red Nissan GTR R35 in a rainy city scene
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- text: >-
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realistic photography of a Infiniti G37s IPL 2010 in black on aftermarket
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wheels lowered
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output:
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url: images/example_30v5f8gp9.png
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base_model:
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- black-forest-labs/FLUX.1-dev
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instance_prompt: a {subject} in a {scene}
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pipeline_tag: text-to-image
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library_name: diffusers
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metrics:
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- FID
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---
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# Test123
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images/example_30v5f8gp9.png
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Git LFS Details
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