Instructions to use UNCANNY69/BERT_Attention with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UNCANNY69/BERT_Attention with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UNCANNY69/BERT_Attention", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("UNCANNY69/BERT_Attention", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update model.py
Browse files
model.py
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@@ -34,7 +34,7 @@ class BertAttentionConfig(PretrainedConfig):
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class BertAttentionForSequenceClassification(PreTrainedModel, metaclass=ABCMeta):
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config_class =
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def __init__(self, config):
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super(BertAttentionForSequenceClassification, self).__init__(config)
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class BertAttentionForSequenceClassification(PreTrainedModel, metaclass=ABCMeta):
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config_class = BertAttentionConfig # Use the appropriate BERT configuration class
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def __init__(self, config):
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super(BertAttentionForSequenceClassification, self).__init__(config)
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