Instructions to use textattack/distilbert-base-uncased-RTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/distilbert-base-uncased-RTE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/distilbert-base-uncased-RTE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/distilbert-base-uncased-RTE") model = AutoModelForSequenceClassification.from_pretrained("textattack/distilbert-base-uncased-RTE") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"finetuning_task": "rte",
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"hidden_dim": 3072,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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"finetuning_task": "glue:rte",
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"hidden_dim": 3072,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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