Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use covalenthq/boredape_diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use covalenthq/boredape_diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("covalenthq/boredape_diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a bayc nft" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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## Model Description
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This DreamBooth model is an exquisite derivative of
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### Training
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## Model Description
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This DreamBooth model is an exquisite derivative of [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5), fine-tuned with an engaging emphasis on the Bored Ape Yacht Club (BAYC) NFT collection. The model's weights were meticulously honed using photos from BAYC NFTs, leveraging the innovative [DreamBooth](https://dreambooth.github.io/) technology to curate a unique, text-to-image synthesis experience.
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### Training
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