class Arguments:
Browse files
app.py
CHANGED
@@ -16,10 +16,28 @@ from hyvideo.constants import NEGATIVE_PROMPT
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from huggingface_hub import snapshot_download
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if torch.cuda.device_count() > 0:
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snapshot_download(repo_id="tencent/HunyuanVideo", repo_type="model", local_dir="ckpts", force_download=True)
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snapshot_download(repo_id="xtuner/llava-llama-3-8b-v1_1-transformers", repo_type="model", local_dir="ckpts/llava-llama-3-8b-v1_1-transformers", force_download=True)
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-
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snapshot_download(repo_id="openai/clip-vit-large-patch14", repo_type="model", local_dir="ckpts/text_encoder_2", force_download=True)
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def initialize_model(model_path):
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from huggingface_hub import snapshot_download
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if torch.cuda.device_count() == 0:
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class Arguments:
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def __init__(self, input_dir, output_dir):
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self.input_dir = input_dir
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self.output_dir = output_dir
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# Create the object
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args = Arguments("ckpts/llava-llama-3-8b-v1_1-transformers", "ckpts/text_encoder")
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preprocess_text_encoder_tokenizer(args)
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if torch.cuda.device_count() > 0:
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snapshot_download(repo_id="tencent/HunyuanVideo", repo_type="model", local_dir="ckpts", force_download=True)
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snapshot_download(repo_id="xtuner/llava-llama-3-8b-v1_1-transformers", repo_type="model", local_dir="ckpts/llava-llama-3-8b-v1_1-transformers", force_download=True)
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class Args:
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def __init__(self, input_dir, output_dir):
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self.input_dir = input_dir
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self.output_dir = output_dir
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# Create the object
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args = Args("ckpts/llava-llama-3-8b-v1_1-transformers", "ckpts/text_encoder")
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preprocess_text_encoder_tokenizer(args)
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snapshot_download(repo_id="openai/clip-vit-large-patch14", repo_type="model", local_dir="ckpts/text_encoder_2", force_download=True)
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def initialize_model(model_path):
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