Instructions to use hamzaMM/questionClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamzaMM/questionClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hamzaMM/questionClassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hamzaMM/questionClassifier") model = AutoModelForSequenceClassification.from_pretrained("hamzaMM/questionClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from hamzaMM/questionClassifier: direct link, hf CLI and curl.
- Browser
- Download file 241 Bytes
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https://huggingface.co/hamzaMM/questionClassifier/resolve/refs%2Fpr%2F2/README.md
- Command line
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hf download hf://hamzaMM/questionClassifier@refs/pr/2/README.md
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curl -L -o README.md https://huggingface.co/hamzaMM/questionClassifier/resolve/refs%2Fpr%2F2/README.md
241 Bytes
| ```python | |
| from transformers import pipeline | |
| pipe = pipeline(model="hamzaMM/questionClassifier", task="text-classification") | |
| def is_question(input: str): | |
| return pipe(input)[0]['label'] == 'LABEL_1' | |
| is_question("How is the weather") | |
| ``` |