Text-to-Image
Diffusers
Safetensors
StableDiffusionXLPipeline
materials
microstructure
electron_micrograph
characterization
scientific_figure_understanding
Instructions to use UniParser/EM3M-Gen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UniParser/EM3M-Gen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("UniParser/EM3M-Gen", 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:
- e05193793089f60ed3f9c151b012ddf14c07ae89a463932a200f928eb1cc40fc
- Size of remote file:
- 246 MB
- SHA256:
- 27a3873859fe9b516fa7eb9d7e8944ff6b2940f8063d7738e68957509026e962
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