Instructions to use engineerA314/Wan2.1-Fun-V1.1-1.3B-InP-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use engineerA314/Wan2.1-Fun-V1.1-1.3B-InP-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("engineerA314/Wan2.1-Fun-V1.1-1.3B-InP-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
File size: 459 Bytes
7decf66 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"_class_name": "WanTransformer3DModel",
"_diffusers_version": "0.37.1",
"in_channels": 36,
"out_channels": 16,
"num_attention_heads": 12,
"attention_head_dim": 128,
"patch_size": [
1,
2,
2
],
"text_dim": 4096,
"freq_dim": 256,
"ffn_dim": 8960,
"num_layers": 30,
"cross_attn_norm": true,
"qk_norm": "rms_norm_across_heads",
"eps": 1e-06,
"image_dim": 1280,
"added_kv_proj_dim": 1536,
"rope_max_seq_len": 1024
} |