Text Classification
Transformers
Safetensors
English
bert
emotion
classification
emojis
emotions
v1.0
sentiment-analysis
nlp
lightweight
chatbot
social-media
mental-health
short-text
emotion-detection
real-time
expressive
ai
machine-learning
english
inference
edge-ai
smart-replies
tone-analysis
Instructions to use boltuix/bert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boltuix/bert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boltuix/bert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boltuix/bert-emotion") model = AutoModelForSequenceClassification.from_pretrained("boltuix/bert-emotion", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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- Check this : [Video documentation](https://youtu.be/FccGKE1kV4Q) [to train own model](https://www.boltuix.com/2021/03/revolutionizing-nlp-deep-dive-into-bert.html)
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We welcome community feedback to enhance BERT-Emotion for IoT and edge applications!
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## Contact
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- Check this : [Video documentation](https://youtu.be/FccGKE1kV4Q) [to train own model](https://www.boltuix.com/2021/03/revolutionizing-nlp-deep-dive-into-bert.html)
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We welcome community feedback to enhance BERT-Emotion for IoT and edge applications!
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## Contact
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