Text Classification
Transformers
Safetensors
PyTorch
English
Hindi
distilbert
emotion-detection
sentiment-analysis
mental-health
emotion-classification
hinglish
Eval Results (legacy)
text-embeddings-inference
Instructions to use Fynman-stack/raven-emotion-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fynman-stack/raven-emotion-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fynman-stack/raven-emotion-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fynman-stack/raven-emotion-distilbert") model = AutoModelForSequenceClassification.from_pretrained("Fynman-stack/raven-emotion-distilbert") - Notebooks
- Google Colab
- Kaggle
Soumyadip Raha
Upload Raven emotion classifier - fine-tuned DistilBERT (97.62% accuracy on personal data)
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