hunyuanvideo text encoder offload

examples/HunyuanVideo/hunyuanvideo_16G.py

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+import torch
+torch.cuda.set_per_process_memory_fraction(1.0, 0)
+from diffsynth import ModelManager, HunyuanVideoPipeline, download_models, save_video
+
+
+download_models(["HunyuanVideo"])
+model_manager = ModelManager()
+
+# The DiT model is loaded in bfloat16.
+model_manager.load_models(
+    [
+        "models/HunyuanVideo/transformers/mp_rank_00_model_states.pt"
+    ],
+    torch_dtype=torch.bfloat16,
+    device="cpu"
+)
+
+# The other modules are loaded in float16.
+model_manager.load_models(
+    [
+        "models/HunyuanVideo/text_encoder/model.safetensors",
+        "models/HunyuanVideo/text_encoder_2",
+        "models/HunyuanVideo/vae/pytorch_model.pt",
+    ],
+    torch_dtype=torch.float16,
+    device="cpu"
+)
+
+# We support LoRA inference. You can use the following code to load your LoRA model.
+# model_manager.load_lora("models/lora/xxx.safetensors", lora_alpha=1.0)
+
+# The computation device is "cuda".
+pipe = HunyuanVideoPipeline.from_model_manager(
+    model_manager,
+    torch_dtype=torch.bfloat16,
+    device="cuda"
+)
+
+# Enjoy!
+prompt = "CG, masterpiece, best quality, solo, long hair, wavy hair, silver hair, blue eyes, blue dress, medium breasts, dress, underwater, air bubble, floating hair, refraction, portrait. The girl's flowing silver hair shimmers with every color of the rainbow and cascades down, merging with the floating flora around her."
+video = pipe(prompt, seed=0, height=720, width=960)
+save_video(video, "video.mp4", fps=30, quality=5)

examples/HunyuanVideo/hunyuanvideo_8G.py

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+import torch
+torch.cuda.set_per_process_memory_fraction(1.0, 0)
+from diffsynth import ModelManager, HunyuanVideoPipeline, download_models, save_video
+
+
+download_models(["HunyuanVideo"])
+model_manager = ModelManager()
+
+# The DiT model is loaded in bfloat16.
+model_manager.load_models(
+    [
+        "models/HunyuanVideo/transformers/mp_rank_00_model_states.pt"
+    ],
+    torch_dtype=torch.bfloat16,
+    device="cpu"
+)
+
+# The other modules are loaded in float16.
+model_manager.load_models(
+    [
+        "models/HunyuanVideo/text_encoder/model.safetensors",
+        "models/HunyuanVideo/text_encoder_2",
+        "models/HunyuanVideo/vae/pytorch_model.pt",
+    ],
+    torch_dtype=torch.float16,
+    device="cpu"
+)
+
+# We support LoRA inference. You can use the following code to load your LoRA model.
+model_manager.load_lora("models/lora/Rem_hunyuan_video_v3.safetensors", lora_alpha=1.0)
+
+# The computation device is "cuda".
+pipe = HunyuanVideoPipeline.from_model_manager(
+    model_manager,
+    torch_dtype=torch.bfloat16,
+    device="cuda"
+)
+
+# Enjoy!
+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."
+video = pipe(prompt, seed=0, height=512, width=512, tile_size=(17, 16, 16), tile_stride=(12, 12, 12))
+save_video(video, "video.mp4", fps=30, quality=5)