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
File size: 476 Bytes
7d38f83 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"_class_name": "AuroraLMTextEncoder",
"_diffusers_version": "0.42.1",
"kind": "lm",
"vocab_size": 12288,
"lm_blocks": 18,
"lm_dim": 768,
"lm_heads": 12,
"lm_ffn_mult": 2.8125,
"lm_norm_eps": 1e-06,
"lm_rope_theta": 100000.0,
"lm_value_residual": true,
"lm_qk_norm": true,
"dim": 768,
"depth": 2,
"heads": 12,
"kv_heads": 4,
"head_dim": 64,
"mlp_hidden": 2048,
"max_tokens": 96,
"bos_id": 12285,
"pad_id": 65535,
"null_id": 65534
} |