Text Classification
Transformers
ONNX
Safetensors
English
Portuguese
bert
classification
questioning
directed
generic
text-embeddings-inference
Instructions to use cnmoro/bert-tiny-question-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnmoro/bert-tiny-question-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cnmoro/bert-tiny-question-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cnmoro/bert-tiny-question-classifier") model = AutoModelForSequenceClassification.from_pretrained("cnmoro/bert-tiny-question-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ceb4689a7190332f03c63d7cc60e65654c0cef5922c5441f14ad6b2ed8e2683
- Size of remote file:
- 17.5 MB
- SHA256:
- 0dad99e2cece21b199cb253a42a1ee4cc8de9cdaf39235cf68e4cb372ae89135
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