mirror of
https://github.com/modelscope/DiffSynth-Studio.git
synced 2026-03-23 00:58:11 +00:00
43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import torch
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torch.cuda.set_per_process_memory_fraction(1.0, 0)
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from diffsynth import ModelManager, HunyuanVideoPipeline, download_models, save_video
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download_models(["HunyuanVideo"])
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model_manager = ModelManager()
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# The DiT model is loaded in bfloat16.
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model_manager.load_models(
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[
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"models/HunyuanVideo/transformers/mp_rank_00_model_states.pt"
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],
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torch_dtype=torch.bfloat16,
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device="cpu"
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)
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# The other modules are loaded in float16.
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model_manager.load_models(
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[
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"models/HunyuanVideo/text_encoder/model.safetensors",
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"models/HunyuanVideo/text_encoder_2",
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"models/HunyuanVideo/vae/pytorch_model.pt",
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],
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torch_dtype=torch.float16,
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device="cpu"
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)
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# We support LoRA inference. You can use the following code to load your LoRA model.
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model_manager.load_lora("models/lora/Rem_hunyuan_video_v3.safetensors", lora_alpha=1.0)
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# The computation device is "cuda".
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pipe = HunyuanVideoPipeline.from_model_manager(
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model_manager,
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torch_dtype=torch.bfloat16,
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device="cuda"
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)
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# Enjoy!
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prompt = "a woman with blue hair wearing a white and black dress, sitting on a bed with a white wall in the background. she is wearing a re:zero starting life in another world rem cosplay costume, complete with a black and white dress, black gloves, and a black bow tie."
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video = pipe(prompt, seed=0, height=512, width=512, tile_size=(17, 16, 16), tile_stride=(12, 12, 12))
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save_video(video, "video.mp4", fps=30, quality=5)
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