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
File size: 486 Bytes
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"_class_name": [
"pipeline",
"MiniT2ITextToImagePipeline"
],
"_diffusers_version": "0.32.0",
"default_num_inference_steps": 100,
"model_type": "l16",
"recommended_guidance_scale": 6.0,
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"T5EncoderModel"
],
"tokenizer": [
"transformers",
"T5Tokenizer"
],
"transformer": [
"transformer_minit2i",
"MiniT2IMMJiTModel"
]
}
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