Text Classification
Transformers
Safetensors
English
modernbert
sentiment-analysis
sentiment
sst-2
sst2
reviews
english
positive-negative
distilbert-sst2-alternative
text-embeddings-inference
Instructions to use AnkitAI/Sensible-ModernBERT-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/Sensible-ModernBERT-Sentiment-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/Sensible-ModernBERT-Sentiment-Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnkitAI/Sensible-ModernBERT-Sentiment-Analysis") model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/Sensible-ModernBERT-Sentiment-Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base": "answerdotai/ModernBERT-base", | |
| "seed": 42, | |
| "task": "sst2", | |
| "val_accuracy": 0.9461009174311926, | |
| "val_f1": 0.9471316085489314, | |
| "incumbent": "distilbert-sst2 = 0.913 on this same validation split" | |
| } |