Text-to-Image
Diffusers
Safetensors
StableDiffusionXLPipeline
materials
microstructure
electron_micrograph
characterization
scientific_figure_understanding
Instructions to use UniParser/UniEM-Gen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UniParser/UniEM-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/UniEM-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
- Draw Things
- DiffusionBee

- Xet hash:
- 5e98e602b098fe2743ec27a44c6b096f5b5e47fad554b145a7c1dfbc32712f4f
- Size of remote file:
- 2.22 MB
- SHA256:
- 4c90aa00a136b70580c5811dfee988644001451553b76f78c801ad7a4ab6b615
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