Image-to-Text
Diffusers
Safetensors
English
uniar
image-generation
image-understanding
image-editing
multimodal
autoregressive
text-to-image
unified-model
Instructions to use ShareLab-SII/UniAR-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShareLab-SII/UniAR-SFT with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShareLab-SII/UniAR-SFT", 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
- Xet hash:
- d7dfb681323f97b667ed899bac832b809e272f66e9b5f1e745f7bb720570a112
- Size of remote file:
- 4.99 GB
- SHA256:
- 4f2751ceeb2a96edd693e539dc5d6bba0b8d3814f49a9b3798403a0cec4b2e3d
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