Text Classification
Transformers
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use pranay-j/bert-base-uncased-google-boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pranay-j/bert-base-uncased-google-boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pranay-j/bert-base-uncased-google-boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pranay-j/bert-base-uncased-google-boolq") model = AutoModelForSequenceClassification.from_pretrained("pranay-j/bert-base-uncased-google-boolq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
updated example
Browse files
README.md
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language:
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widget:
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example_title: "Bool QA"
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license: apache-2.0
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base_model: bert-base-uncased
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language:
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- en
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widget:
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- text: "did abraham lincoln write the letter in saving private ryan <sep> In the 1998 war film Saving Private Ryan, General George Marshall (played by Harve Presnell) reads the Bixby letter to his officers before giving the order to find and send home Private James Francis Ryan after Ryan's three brothers died in battle."
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example_title: "Bool QA"
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license: apache-2.0
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base_model: bert-base-uncased
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