Instructions to use lekhnathrijal/bert-question-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lekhnathrijal/bert-question-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lekhnathrijal/bert-question-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lekhnathrijal/bert-question-classifier") model = AutoModelForSequenceClassification.from_pretrained("lekhnathrijal/bert-question-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lekhnathrijal/bert-question-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/lekhnathrijal/bert-question-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://lekhnathrijal/bert-question-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lekhnathrijal/bert-question-classifier/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 6acec6b732c4c97d9c998b3ab8b8b66c69bddd5bdb1028ec876fc1ef7adef549
- Size of remote file:
- 5.43 kB
- SHA256:
- 5fe8a476c46a33681ad99692b16ee26a4f109b597e0629d5cda665ddbe872311
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.