Instructions to use Yaquv/rickthenpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yaquv/rickthenpc 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("Yaquv/rickthenpc") prompt = "Bald purple Rick" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
add: model_index.json
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by ferrymangmi - opened
- model_index.json +5 -0
model_index.json
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{
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"_class_name": "StableDiffusionPipeline",
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"model_type": "StableDiffusion",
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"checkpoint": "rickthenpc.safetensors"
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}
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