Text Classification
Transformers
Safetensors
English
bert
finbert
finance
sentiment
sentiment-analysis
financial-sentiment
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ENTUM-AI/FinBERT-Multi")
model = AutoModelForSequenceClassification.from_pretrained("ENTUM-AI/FinBERT-Multi")Quick Links
🎯 FinBERT-Multi
Financial sentiment analysis model. Fine-tuned ProsusAI/finbert on 143K+ samples from 5 combined financial datasets.
The model outputs softmax outputs for three sentiment classes: Positive, Negative, Neutral.
🚀 Usage
from transformers import pipeline
classifier = pipeline("text-classification", model="ENTUM-AI/FinBERT-Multi")
classifier("Stock price soars on record-breaking earnings report")
# [{'label': 'Positive', 'score': 0.99}]
classifier("Company announces quarterly earnings results")
# [{'label': 'Neutral', 'score': 0.98}]
classifier("Revenue decline signals weakening market position")
# [{'label': 'Negative', 'score': 0.97}]
📊 Training Data
| Dataset | Samples |
|---|---|
| FinanceInc/auditor_sentiment | ~4.8K |
| nickmuchi/financial-classification | ~5K |
| warwickai/financial_phrasebank_mirror | ~4.8K |
| NOSIBLE/financial-sentiment | ~100K |
| TimKoornstra/financial-tweets-sentiment | ~38K |
⚠️ Limitations
- English only
- Downloads last month
- 20
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ENTUM-AI/FinBERT-Multi")