Instructions to use Sourabh2/Human_Face_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Sourabh2/Human_Face_generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Sourabh2/Human_Face_generator", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
language: en
Example Usage
from diffusers import StableDiffusionPipeline
import torch
model_path = "Sourabh2/Human_Face_generator"
pipe = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16)
pipe.to("cuda")
prompt = "a man with blonde hair and beard"
image = pipe(prompt=prompt).images[0]
image.save("face.png")
Example Output
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