Text-to-Image
Diffusers
Safetensors
English
AuroraIMG2Pipeline
flow-matching
rectified-flow
diffusion-transformer
from-scratch
muon
diloco
repa
custom_code
Instructions to use cpral/IMG-253M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cpral/IMG-253M with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cpral/IMG-253M", 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 Settings
- Draw Things
- DiffusionBee
Download model_index.json from cpral/IMG-253M: direct link, hf CLI and curl.
- Browser
- Download file 333 Bytes
-
https://huggingface.co/cpral/IMG-253M/resolve/main/model_index.json
- Command line
-
hf download hf://cpral/IMG-253M/model_index.json
-
curl -L -o model_index.json https://huggingface.co/cpral/IMG-253M/resolve/main/model_index.json
333 Bytes
| { | |
| "_class_name": "AuroraIMG2Pipeline", | |
| "_diffusers_version": "0.42.1", | |
| "text_encoder": [ | |
| "pipeline", | |
| "AuroraLMTextEncoder" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "PreTrainedTokenizerFast" | |
| ], | |
| "transformer": [ | |
| "pipeline", | |
| "AuroraDenoiser" | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKLFlux2" | |
| ] | |
| } |