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Author SHA1 Message Date
bigcat88 7f71507c82 fix(api-nodes): use a unique name for uploading audio files 2026-01-10 09:39:29 +02:00
7 changed files with 8 additions and 10 deletions

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@ -183,7 +183,7 @@ Simply download, extract with [7-Zip](https://7-zip.org) or with the windows exp
If you have trouble extracting it, right click the file -> properties -> unblock
The portable above currently comes with python 3.13 and pytorch cuda 13.0. Update your Nvidia drivers if it doesn't start.
Update your Nvidia drivers if it doesn't start.
#### Alternative Downloads:
@ -212,7 +212,7 @@ Python 3.14 works but you may encounter issues with the torch compile node. The
Python 3.13 is very well supported. If you have trouble with some custom node dependencies on 3.13 you can try 3.12
torch 2.4 and above is supported but some features might only work on newer versions. We generally recommend using the latest major version of pytorch with the latest cuda version unless it is less than 2 weeks old.
torch 2.4 and above is supported but some features might only work on newer versions. We generally recommend using the latest major version of pytorch unless it is less than 2 weeks old.
### Instructions:

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@ -237,8 +237,6 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
else:
dit_config["vec_in_dim"] = None
dit_config["num_heads"] = dit_config["hidden_size"] // sum(dit_config["axes_dim"])
dit_config["depth"] = count_blocks(state_dict_keys, '{}double_blocks.'.format(key_prefix) + '{}.')
dit_config["depth_single_blocks"] = count_blocks(state_dict_keys, '{}single_blocks.'.format(key_prefix) + '{}.')
if '{}distilled_guidance_layer.0.norms.0.scale'.format(key_prefix) in state_dict_keys or '{}distilled_guidance_layer.norms.0.scale'.format(key_prefix) in state_dict_keys: #Chroma

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@ -368,7 +368,7 @@ try:
if any((a in arch) for a in ["gfx90a", "gfx942", "gfx1100", "gfx1101", "gfx1151"]): # TODO: more arches, TODO: gfx950
ENABLE_PYTORCH_ATTENTION = True
if rocm_version >= (7, 0):
if any((a in arch) for a in ["gfx1200", "gfx1201"]):
if any((a in arch) for a in ["gfx1201"]):
ENABLE_PYTORCH_ATTENTION = True
if torch_version_numeric >= (2, 7) and rocm_version >= (6, 4):
if any((a in arch) for a in ["gfx1200", "gfx1201", "gfx950"]): # TODO: more arches, "gfx942" gives error on pytorch nightly 2.10 1013 rocm7.0

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@ -1059,9 +1059,9 @@ def detect_te_model(sd):
return TEModel.JINA_CLIP_2
if "encoder.block.23.layer.1.DenseReluDense.wi_1.weight" in sd:
weight = sd["encoder.block.23.layer.1.DenseReluDense.wi_1.weight"]
if weight.shape[0] == 10240:
if weight.shape[-1] == 4096:
return TEModel.T5_XXL
elif weight.shape[0] == 5120:
elif weight.shape[-1] == 2048:
return TEModel.T5_XL
if 'encoder.block.23.layer.1.DenseReluDense.wi.weight' in sd:
return TEModel.T5_XXL_OLD

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@ -36,7 +36,7 @@ def te(dtype_t5=None, t5_quantization_metadata=None):
if t5_quantization_metadata is not None:
model_options = model_options.copy()
model_options["t5xxl_quantization_metadata"] = t5_quantization_metadata
if dtype_t5 is not None:
if dtype is None:
dtype = dtype_t5
super().__init__(device=device, dtype=dtype, model_options=model_options)
return CosmosTEModel_

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@ -32,7 +32,7 @@ def mochi_te(dtype_t5=None, t5_quantization_metadata=None):
if t5_quantization_metadata is not None:
model_options = model_options.copy()
model_options["t5xxl_quantization_metadata"] = t5_quantization_metadata
if dtype_t5 is not None:
if dtype is None:
dtype = dtype_t5
super().__init__(device=device, dtype=dtype, model_options=model_options)
return MochiTEModel_

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@ -36,7 +36,7 @@ def pixart_te(dtype_t5=None, t5_quantization_metadata=None):
if t5_quantization_metadata is not None:
model_options = model_options.copy()
model_options["t5xxl_quantization_metadata"] = t5_quantization_metadata
if dtype_t5 is not None:
if dtype is None:
dtype = dtype_t5
super().__init__(device=device, dtype=dtype, model_options=model_options)
return PixArtTEModel_