Instructions to use lightx2v/Wan2.1-T2V-1.3B-longcat-step500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Wan2.1-T2V-1.3B-longcat-step500 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B-Diffusers", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Wan2.1-T2V-1.3B-longcat-step500") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
File size: 802 Bytes
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"alpha_pattern": {},
"auto_mapping": {
"base_model_class": "WanTransformer3DModel",
"parent_library": "diffusers.models.transformers.transformer_wan"
},
"base_model_name_or_path": null,
"bias": "none",
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": "gaussian",
"layer_replication": null,
"layers_pattern": null,
"layers_to_transform": null,
"loftq_config": {},
"lora_alpha": 64,
"lora_dropout": 0.0,
"megatron_config": null,
"megatron_core": "megatron.core",
"modules_to_save": null,
"peft_type": "LORA",
"r": 128,
"rank_pattern": {},
"revision": null,
"target_modules": [
"to_v",
"to_out.0",
"net.0.proj",
"net.2",
"to_q",
"to_k"
],
"task_type": null,
"use_dora": false,
"use_rslora": false
} |