Instructions to use savasy/bert-base-turkish-sentiment-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use savasy/bert-base-turkish-sentiment-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="savasy/bert-base-turkish-sentiment-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("savasy/bert-base-turkish-sentiment-cased") model = AutoModelForSequenceClassification.from_pretrained("savasy/bert-base-turkish-sentiment-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
Request: DOI
#3
by beratcabuk - opened
Hi there, I would like to use this work in my undergrad thesis, so it'd be perfect (for ease of proper citation) if there was a DOI number for it. Is it possible to generate one?
Hi Berat,
You can cite my book as follows:
@book {yildirim2021mastering,
title={Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques},
author={Yildirim, Savas and Asgari-Chenaghlu, Meysam},
year={2021},
publisher={Packt Publishing Ltd}
}