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
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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## Model description
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- **Model type:** Text Classification model
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- **Language(s) (NLP):** English
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- **License:** Apache 2.0
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## Intended uses & limitations
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## Training and evaluation data
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- [Dataset](https://huggingface.co/datasets/google/boolq)
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## Training procedure
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