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:
- a594b61e66e0eb332adbf5d29ca2abd3e51af1e5db110aac47638b248ba58775
- Size of remote file:
- 6.6 MB
- SHA256:
- 52d6b8d6f2b2c6a27b6dc57802429e9afab9fade7fd747029d4aa13c82c09794
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