Text-to-Image
Diffusers
Safetensors
Flux2KleinPipeline
flux2
flux2-klein
diffusionnft
reinforcement-learning
Instructions to use kimi000/velvet-comet-51 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kimi000/velvet-comet-51 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kimi000/velvet-comet-51", 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

- Xet hash:
- b6d8f644bdff103879ec21f8a41cd6b172f4c3267d563ba045024c4ed60f7c03
- Size of remote file:
- 377 kB
- SHA256:
- 1e70ee416ac074a4439b09472e89b5ad63f056abea86080a46abebf43e0aeb4f
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