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
Update README.md
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README.md
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@@ -135,7 +135,7 @@ Full project documentation, hardware build guide, and source code:
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@misc{dcode2024,
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author = {Teddy Warner},
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title = {dcode: Text-to-Gcode Diffusion Model},
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-
year = {
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url = {https://teddywarner.org/Projects/Polargraph/#dcode}
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}
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```
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@misc{dcode2024,
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author = {Teddy Warner},
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title = {dcode: Text-to-Gcode Diffusion Model},
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year = {2026},
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url = {https://teddywarner.org/Projects/Polargraph/#dcode}
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}
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```
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