Text Classification
Transformers
PyTorch
Safetensors
English
bert
finance
financial
news
sentiment-analysis
finbert
transfomer
financial-news
financial-news-sentiment
text-embeddings-inference
Instructions to use project-aps/finbert-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use project-aps/finbert-finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="project-aps/finbert-finetune")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("project-aps/finbert-finetune") model = AutoModelForSequenceClassification.from_pretrained("project-aps/finbert-finetune") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b359c32aa5b6a413f2c7ec7af082c295bebd10a677ec391499f727f495ae43b2
- Size of remote file:
- 438 MB
- SHA256:
- e97649a55e64b25d25af86321525b3b7265734b7fde758be67a02fe9226310a4
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