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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92512a21d23dc5a1b70f43322b9d027fa9715fafb2a0acdf3593c084bcf1eb45
- Size of remote file:
- 4.49 MB
- SHA256:
- 659c83b11f04eb93079315c8ca9115aa77cb9e2159dc474c8aded4bd36589a34
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