Instructions to use Akshayextreme/SemEval_2015_PIT_crossencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akshayextreme/SemEval_2015_PIT_crossencoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Akshayextreme/SemEval_2015_PIT_crossencoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Akshayextreme/SemEval_2015_PIT_crossencoder") model = AutoModelForSequenceClassification.from_pretrained("Akshayextreme/SemEval_2015_PIT_crossencoder") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 5fe6b42
Pushing trained model
Browse files- config.json +1 -1
config.json
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.24.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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