Text Classification
Transformers
Safetensors
Chinese
bert
financial-sentiment-analysis
sentiment-analysis
Instructions to use yiyanghkust/finbert-tone-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yiyanghkust/finbert-tone-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yiyanghkust/finbert-tone-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yiyanghkust/finbert-tone-chinese") model = AutoModelForSequenceClassification.from_pretrained("yiyanghkust/finbert-tone-chinese") - Inference
- Notebooks
- Google Colab
- Kaggle
谢谢伟大的作者!
#2
by XiaoXuMeiYouNLP - opened
谢谢伟大的作者!我想在自己的研究里引用这个模型,请问可以有引用信息吗?QAQ
Thanks for your contribution! I want to cite this model in a paper, and could you provide any citation info? (if possible QAQ
Thanks. You can cite the following.
Yang, Yi, Mark Christopher Siy Uy, and Allen Huang. "Finbert: A pretrained language model for financial communications." arXiv preprint arXiv:2006.08097 (2020).