Instructions to use Yaquv/rick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yaquv/rick 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/rick") prompt = "Rick" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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Weights for this model are available in Safetensors format.
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[Download](/Yaquv/rick/tree/main) them in the Files & versions tab.
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## Training at fal.ai
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Training was done using [fal.ai/models/fal-ai/flux-lora-fast-training](https://fal.ai/models/fal-ai/flux-lora-fast-training).
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Weights for this model are available in Safetensors format.
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[Download](/Yaquv/rick/tree/main) them in the Files & versions tab.
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