Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use imann63/trained_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use imann63/trained_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("imann63/trained_models", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a special powerline station" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.safetensors from imann63/trained_models: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/imann63/trained_models/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://imann63/trained_models/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/imann63/trained_models/resolve/main/vae/diffusion_pytorch_model.safetensors
335 MB
- Xet hash:
- 1d076cb26577e80732318fd5215b400700e87cba063e3825a61c7cafdeec0147
- Size of remote file:
- 335 MB
- SHA256:
- 86a6170968f284b6c0c111e2611c806a04102e2a48790ebd1d490ca78040d2bb
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