Instructions to use BiliSakura/MiniT2I-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/MiniT2I-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/MiniT2I-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "A lonely astronaut standing on a quiet beach under two moons." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "MiniT2IMMJiTModel", | |
| "_diffusers_version": "0.35.2", | |
| "cfg_channels": 3, | |
| "cfg_interval": [ | |
| 0.0, | |
| 1.0 | |
| ], | |
| "cond_vec_size": 768, | |
| "depth_double": 17, | |
| "head_dim": 64, | |
| "hidden_size": 768, | |
| "image_size": 512, | |
| "in_channels": 3, | |
| "llm": "google/flan-t5-large", | |
| "mlp_ratio": 2.6666666666666665, | |
| "n_T": 100, | |
| "num_heads": 12, | |
| "patch_size": 16, | |
| "pca_channels": 128, | |
| "prediction": "x", | |
| "prompt_length": 256, | |
| "sampler": "euler", | |
| "txt_hidden_size": 768, | |
| "txt_input_size": 1024, | |
| "txt_preamble_depth": 2 | |
| } | |