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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 200c5586ca4a0a7111e16b7ec1702db05c9c3eef4a908dd7a233975fc9124058
- Size of remote file:
- 4.98 kB
- SHA256:
- 772843bd8850c3c86ff160e8c7e9457e2b3e5a7bf7bf27f2b2a6453662366a70
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