Instructions to use hw2942/bert-base-chinese-finetuning-financial-news-sentiment-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hw2942/bert-base-chinese-finetuning-financial-news-sentiment-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hw2942/bert-base-chinese-finetuning-financial-news-sentiment-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hw2942/bert-base-chinese-finetuning-financial-news-sentiment-v2") model = AutoModelForSequenceClassification.from_pretrained("hw2942/bert-base-chinese-finetuning-financial-news-sentiment-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
Data source: hw2942/financial-news-sentiment
Pre-trained model for fine-tuning: bert-base-chinese
Fine-tuned data: 2000 for train, 329 for validation
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