Instructions to use snake7gun/Bernini-R-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use snake7gun/Bernini-R-tiny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("snake7gun/Bernini-R-tiny", 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
File size: 385 Bytes
91e4ae4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"model_type": "bernini_renderer",
"architectures": [
"BerniniRendererModel"
],
"wan22_base": "D:\\openvino_notebooks\\notebooks\\bernini-r-image-video\\Bernini-R-tiny",
"skip_transformer_1": false,
"skip_transformer_2": true,
"switch_dit_boundary": 0,
"max_sequence_length": 512,
"shift": 3.0,
"use_unipc": true,
"use_src_id_rotary_emb": true
} |