Spaces:
Running
on
Zero
Running
on
Zero
test t5
Browse files
stable/stable_audio_tools/models/conditioners.py
CHANGED
@@ -5,7 +5,7 @@ import logging, warnings
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import string
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import typing as tp
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import gc
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-
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from .adp import NumberEmbedder
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from ..inference.utils import set_audio_channels
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from .factory import create_pretransform_from_config
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@@ -283,6 +283,8 @@ class T5Conditioner(Conditioner):
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# self.tokenizer = T5Tokenizer.from_pretrained(t5_model_name, model_max_length = max_length)
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# model = T5EncoderModel.from_pretrained(t5_model_name, max_length=max_length).train(enable_grad).requires_grad_(enable_grad)
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self.tokenizer = AutoTokenizer.from_pretrained(t5_model_name)
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ckpt = torch.load('../try_t5.pt')
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model = T5EncoderModel.from_pretrained(t5_model_name).train(enable_grad).requires_grad_(enable_grad).to(torch.float16)
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model.load_state_dict(ckpt,strict=True)
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import string
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import typing as tp
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import gc
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import os
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from .adp import NumberEmbedder
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from ..inference.utils import set_audio_channels
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from .factory import create_pretransform_from_config
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# self.tokenizer = T5Tokenizer.from_pretrained(t5_model_name, model_max_length = max_length)
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# model = T5EncoderModel.from_pretrained(t5_model_name, max_length=max_length).train(enable_grad).requires_grad_(enable_grad)
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self.tokenizer = AutoTokenizer.from_pretrained(t5_model_name)
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cwd = os.getcwd()
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print("==========", cwd)
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ckpt = torch.load('../try_t5.pt')
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model = T5EncoderModel.from_pretrained(t5_model_name).train(enable_grad).requires_grad_(enable_grad).to(torch.float16)
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model.load_state_dict(ckpt,strict=True)
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