| import torch |
| import json |
| from diffsynth.utils.data import save_video |
| from diffsynth.pipelines.lingbot_video import LingBotVideoPipeline, ModelConfig |
| from modelscope import dataset_snapshot_download |
|
|
|
|
| pipe = LingBotVideoPipeline.from_pretrained( |
| torch_dtype=torch.bfloat16, |
| device="cuda", |
| model_configs=[ |
| ModelConfig(model_id="Robbyant/lingbot-video-dense-1.3b", origin_file_pattern="transformer/diffusion_pytorch_model.safetensors"), |
| ModelConfig(model_id="Qwen/Qwen3-VL-4B-Instruct", origin_file_pattern="*.safetensors"), |
| ModelConfig(model_id="Robbyant/lingbot-video-dense-1.3b", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"), |
| ], |
| processor_config=ModelConfig(model_id="Qwen/Qwen3-VL-4B-Instruct", origin_file_pattern=""), |
| ) |
| pipe.load_lora(pipe.dit, './models/train/lingbot-video-dense-1.3b_t2v_split/epoch-4.safetensors', alpha=1) |
| dataset_snapshot_download( |
| dataset_id="DiffSynth-Studio/diffsynth_example_dataset", |
| local_dir="data/diffsynth_example_dataset", |
| allow_file_pattern="lingbot_video/lingbot-video-dense-1.3b_t2v/*", |
| ) |
| with open("data/diffsynth_example_dataset/lingbot_video/lingbot-video-dense-1.3b_t2v/t2v_example_1.json", "r", encoding="utf-8") as f: |
| caption = json.load(f) |
|
|
| video = pipe( |
| prompt=caption, |
| negative_prompt=pipe.default_negative_prompt, |
| height=480, width=832, num_frames=81, |
| num_inference_steps=40, cfg_scale=3.0, |
| seed=0, |
| ) |
| save_video(video, 'split_training_lingbot-video-dense-1.3b_t2v.mp4', fps=15, quality=10) |
|
|
