Text Classification
Transformers
PyTorch
Safetensors
English
bert
neural-search-query-classification
neural-search
Instructions to use shahrukhx01/question-vs-statement-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahrukhx01/question-vs-statement-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shahrukhx01/question-vs-statement-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shahrukhx01/question-vs-statement-classifier") model = AutoModelForSequenceClassification.from_pretrained("shahrukhx01/question-vs-statement-classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01b1803718a3120c255870788a598232d463b4ddead07c34f6e39e6241cd1aa1
- Size of remote file:
- 44.7 MB
- SHA256:
- e47836a61bc13290316c2029d3855a3b6d2094910e3a13358bee83e63f0125d4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.