Instructions to use MeiGen-AI/PosterOmni_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MeiGen-AI/PosterOmni_v1 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("MeiGen-AI/PosterOmni_v1", 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
| { | |
| "_class_name": "QwenImageTransformer2DModel", | |
| "_diffusers_version": "0.37.0.dev0", | |
| "_name_or_path": "/mnt/dolphinfs/hdd_pool/docker/user/hadoop-mtcv/sixiangchen/posteromni/merged_lora/qwen-2511_student_distill_24000_9000_0203/transformer", | |
| "attention_head_dim": 128, | |
| "axes_dims_rope": [ | |
| 16, | |
| 56, | |
| 56 | |
| ], | |
| "guidance_embeds": false, | |
| "in_channels": 64, | |
| "joint_attention_dim": 3584, | |
| "num_attention_heads": 24, | |
| "num_layers": 60, | |
| "out_channels": 16, | |
| "patch_size": 2, | |
| "use_additional_t_cond": false, | |
| "use_layer3d_rope": false, | |
| "zero_cond_t": true | |
| } | |