Text Classification
Transformers
Safetensors
English
bert
finbert
finance
sentiment
sentiment-analysis
financial-sentiment
text-embeddings-inference
Instructions to use ENTUM-AI/FinBERT-Multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENTUM-AI/FinBERT-Multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ENTUM-AI/FinBERT-Multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ENTUM-AI/FinBERT-Multi") model = AutoModelForSequenceClassification.from_pretrained("ENTUM-AI/FinBERT-Multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47874347896f5e12b3802e8926f8d82a9388afd7a6acbb3d8baa8485a5130377
- Size of remote file:
- 438 MB
- SHA256:
- ca760fd60c4883c1a4e536abfaf88faf653e01c4d3d56ad95ee0ed31b116798b
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