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
Commit ·
b57e04e
1
Parent(s): a639693
add model
Browse files- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
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{"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "prajjwal1/bert-mini"}
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vocab.txt
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