Text Classification
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bert
emotion-detection
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("KEERTHANA6805/bert-emotion")
model = AutoModelForSequenceClassification.from_pretrained("KEERTHANA6805/bert-emotion", device_map="auto")Quick Links
BERT Emotion Classifier
This model classifies text into 6 emotion categories:
- joy
- sadness
- anger
- fear
- love
- surprise
Model: bert-base-uncased
Dataset: emotion (Hugging Face datasets library)
✅ Usage Example
from transformers import pipeline
classifier = pipeline("text-classification", model="KEERTHANA6805/bert-emotion")
classifier("I am so happy today!")
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Model tree for KEERTHANA6805/bert-emotion
Base model
google-bert/bert-base-uncased
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KEERTHANA6805/bert-emotion")