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
Sensible series branding + rename refs
Browse files
README.md
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- distilbert-sst2-alternative
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---
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#
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### The modern replacement for the classic SST-2 sentiment model — **0.946 vs 0.913** on the exact same benchmark, one `pipeline()` line.
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```python
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from transformers import pipeline
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clf = pipeline("text-classification", model="AnkitAI/ModernBERT-Sentiment-Analysis")
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clf("This movie was absolutely wonderful!")
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# [{'label': 'positive', 'score': 0.99}]
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```
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## 📖 Citation
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```bibtex
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@misc{
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author = {Aglawe, Ankit},
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title = {ModernBERT Sentiment Analysis},
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year = {2026},
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publisher = {Hugging Face},
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url = {https://huggingface.co/AnkitAI/ModernBERT-Sentiment-Analysis}
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}
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```
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- distilbert-sst2-alternative
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---
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# 🦉 Sensible — ModernBERT Sentiment Analysis
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### The modern replacement for the classic SST-2 sentiment model — **0.946 vs 0.913** on the exact same benchmark, one `pipeline()` line.
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```python
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from transformers import pipeline
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clf = pipeline("text-classification", model="AnkitAI/Sensible-ModernBERT-Sentiment-Analysis")
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clf("This movie was absolutely wonderful!")
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# [{'label': 'positive', 'score': 0.99}]
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```
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## 📖 Citation
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```bibtex
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@misc{sensiblesentiment2026,
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author = {Aglawe, Ankit},
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title = {Sensible: ModernBERT Sentiment Analysis},
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year = {2026},
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publisher = {Hugging Face},
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url = {https://huggingface.co/AnkitAI/Sensible-ModernBERT-Sentiment-Analysis}
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}
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```
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