Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
Instructions to use SidXXD/Albert_Einstein with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/Albert_Einstein with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/Albert_Einstein", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_custom_diffusion_weights.bin from SidXXD/Albert_Einstein: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/Albert_Einstein/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/Albert_Einstein/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/Albert_Einstein/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- 5c4db311a95c09f50c6a2166d522cb226e20126022454cd51819d484287e12fc
- Size of remote file:
- 76.7 MB
- SHA256:
- 954be39396e3d16556567924de59f86a8ae253fb0cc7204649325d90a61fc1e3
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