Instructions to use stabilityai/sd-vae-ft-ema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stabilityai/sd-vae-ft-ema 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/sd-vae-ft-ema", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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WebUIs build on top of diffusers start to rely on the HF Hub client library to filter for models. This one should not be displayed when listing "text-to-image" models: ```py import huggingface_hub as hf hf_api = hf.HfApi() model_filter = hf.ModelFilter( model_name="", task='text-to-image', tags='stable-diffusion', library=['diffusers', 'stable-diffusion'], ) res = hf_api.list_models(filter=model_filter, full=True, limit=200, sort="downloads", direction=-1) ```f04b2c4
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Adding `safetensors` variant of this model (#2)
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- Fix link in model card (884f8b9f06faf16fa8050873d1de97e0a9d45c45) Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.huggingface.co>d744379
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