Text-to-Image
Diffusers
PyTorch
gcode
cnc
plotter
polargraph
stable-diffusion
text-to-gcode
diffusion
Instructions to use twarner/dcode-sd-gcode-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use twarner/dcode-sd-gcode-v3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("twarner/dcode-sd-gcode-v3", 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:
- 4a3284d4df80583aca63216f3a898d16f20dabc654c9b1847ee8dc4a1c18b1ca
- Size of remote file:
- 2.81 GB
- SHA256:
- 4632c26f22caad3d31d8cd7498e2dea00a6eb3bfb7973a276b0040ef7258cb81
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