Instructions to use Cainiao-AI/TAAS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cainiao-AI/TAAS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Cainiao-AI/TAAS", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Cainiao-AI/TAAS", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update graphormer.py
Browse files- graphormer.py +1 -1
graphormer.py
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@@ -5,7 +5,7 @@ from torch.nn import Parameter
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from torch.nn.init import normal_
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import torch.utils.checkpoint
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from torch import Tensor, device
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from TAAS_utils import *
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from transformers.modeling_utils import ModuleUtilsMixin
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from fairseq import utils
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from fairseq.models import (
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from torch.nn.init import normal_
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import torch.utils.checkpoint
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from torch import Tensor, device
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from .TAAS_utils import *
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from transformers.modeling_utils import ModuleUtilsMixin
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from fairseq import utils
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from fairseq.models import (
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