Image-to-Image
Diffusers
Safetensors
PyTorch
English
image-generation
virtual-try-on
virtual-try-off
diffusion
dit
stable-diffusion-3
multimodal
fashion
Instructions to use rushabh14/TEMU-VTOFF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rushabh14/TEMU-VTOFF with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rushabh14/TEMU-VTOFF", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 442 Bytes
b03f48b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"_class_name": "SD3Transformer2DModel",
"_diffusers_version": "0.33.0.dev0",
"_name_or_path": "stabilityai/stable-diffusion-3-medium-diffusers",
"attention_head_dim": 64,
"caption_projection_dim": 1536,
"in_channels": 33,
"joint_attention_dim": 4096,
"num_attention_heads": 24,
"num_layers": 24,
"out_channels": 16,
"patch_size": 2,
"pooled_projection_dim": 2048,
"pos_embed_max_size": 192,
"sample_size": 128
}
|