Instructions to use asvin-kumar/cnh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use asvin-kumar/cnh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("asvin-kumar/cnh") 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
- Xet hash:
- d38bfa5fa5e4ceba7fbea70076e1d5eea30e68b78cc462a5fa44d090d1432cc1
- Size of remote file:
- 6.6 MB
- SHA256:
- f6f4f62777911edeb04625b81fd149f9fc991325d14c222d9b631fb723a9fe30
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