Text Classification
Transformers
Safetensors
English
Portuguese
roberta
classification
questioning
directed
generic
text-embeddings-inference
Instructions to use cnmoro/granite-question-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnmoro/granite-question-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cnmoro/granite-question-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cnmoro/granite-question-classifier") model = AutoModelForSequenceClassification.from_pretrained("cnmoro/granite-question-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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The accuracy achieved during training was 94%.
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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The accuracy achieved during training was 94%.
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This model is designed to be an upgrade to the previous model: https://huggingface.co/cnmoro/bert-tiny-question-classifier
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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