Text Classification
Transformers
PyTorch
Safetensors
English
bert
neural-search-query-classification
neural-search
Instructions to use shahrukhx01/bert-mini-finetune-question-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahrukhx01/bert-mini-finetune-question-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shahrukhx01/bert-mini-finetune-question-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shahrukhx01/bert-mini-finetune-question-detection") model = AutoModelForSequenceClassification.from_pretrained("shahrukhx01/bert-mini-finetune-question-detection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
TOKEN LIMIT
#1
by Mike3tdd - opened
hello what's the maximum input sequence tokens and output sequence
Hi,
For output, it is a binary classifier outputting whether the input sequence is a question or not.
For the input as it is the fine-tuned version of prajjwal1/bert-mini it is unclear in its documentation what was the original input token limit, however, i fine-tuned it with a max sequence length of 512.
shahrukhx01 changed discussion status to closed