Text Classification
Transformers
ONNX
Safetensors
PyTorch
English
multi-label-classification
multi-class-classification
emotion
bert
go_emotions
emotion-classification
sentiment-analysis
tensorflow
Eval Results (legacy)
Instructions to use logasanjeev/bert-emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use logasanjeev/bert-emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="logasanjeev/bert-emotion-classifier")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("logasanjeev/bert-emotion-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update LICENSE
Browse files
LICENSE
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MIT License
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Copyright (c) 2025
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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MIT License
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Copyright (c) 2025 Ravindran LogaSanjeev
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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