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modified: src/flux/util.py
Browse files- src/flux/__pycache__/__init__.cpython-310.pyc +0 -0
- src/flux/__pycache__/_version.cpython-310.pyc +0 -0
- src/flux/__pycache__/math.cpython-310.pyc +0 -0
- src/flux/__pycache__/model.cpython-310.pyc +0 -0
- src/flux/__pycache__/sampling.cpython-310.pyc +0 -0
- src/flux/__pycache__/util.cpython-310.pyc +0 -0
- src/flux/modules/__pycache__/autoencoder.cpython-310.pyc +0 -0
- src/flux/modules/__pycache__/conditioner.cpython-310.pyc +0 -0
- src/flux/modules/__pycache__/layers.cpython-310.pyc +0 -0
- src/flux/util.py +1 -1
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src/flux/util.py
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@@ -131,7 +131,7 @@ def load_flow_model(name: str, device: str | torch.device = "cuda", hf_download:
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def load_t5(device: str | torch.device = "cuda", max_length: int = 77) -> HFEmbedder:
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# max length 64, 128, 256 and 512 should work (if your sequence is short enough)
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return HFEmbedder("google/t5-v1_1-
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#return HFEmbedder("/homedata/HuggingFace/black-forest-labs/FLUX.1-dev/text_encoder_2", max_length=max_length, is_clip=False, torch_dtype=torch.bfloat16).to(device)
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def load_t5(device: str | torch.device = "cuda", max_length: int = 77) -> HFEmbedder:
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# max length 64, 128, 256 and 512 should work (if your sequence is short enough)
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return HFEmbedder("google/t5-v1_1-xxl", max_length=max_length, is_clip=False, torch_dtype=torch.bfloat16).to(device)
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#return HFEmbedder("/homedata/HuggingFace/black-forest-labs/FLUX.1-dev/text_encoder_2", max_length=max_length, is_clip=False, torch_dtype=torch.bfloat16).to(device)
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