Text Classification
Transformers
Safetensors
English
modernbert
financial-sentiment-analysis
sentiment-analysis
financial-news
finance
stocks
trading
finbert-alternative
sentiment
fintech
news
text-embeddings-inference
Instructions to use AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis") model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 481 Bytes
26c955d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | {
"ProsusAI/finbert": {
"accuracy": 0.8799171842650103,
"macro_f1": 0.8760718217635312,
"confusion": [
[
60,
0,
0
],
[
14,
240,
33
],
[
2,
9,
125
]
]
},
"AnkitAI/distilbert-base-uncased-financial-news-sentiment-analysis": {
"accuracy": 0.8322981366459627,
"macro_f1": 0.8063650452813015,
"confusion": [
[
46,
8,
6
],
[
10,
257,
20
],
[
1,
36,
99
]
]
}
} |