Instructions to use AI4free/emo-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4free/emo-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AI4free/emo-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AI4free/emo-Classification") model = AutoModelForSequenceClassification.from_pretrained("AI4free/emo-Classification") - Notebooks
- Google Colab
- Kaggle
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# emo-Classification
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Welcome to the **emo-Classification** model by [AI4free](https://huggingface.co/AI4free)! This model is designed for sentiment analysis, specifically to classify emotions based on textual input. By utilizing cutting-edge natural language processing techniques, this model helps in identifying the emotional tone of sentences, making it ideal for various applications in social media monitoring, customer feedback analysis, and more.
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## Acknowledgments
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We would like to thank the Hugging Face community for their support and contributions to the development of this model.
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pipeline_tag: text-classification
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library_name: transformers
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---
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# emo-Classification
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Welcome to the **emo-Classification** model by [AI4free](https://huggingface.co/AI4free)! This model is designed for sentiment analysis, specifically to classify emotions based on textual input. By utilizing cutting-edge natural language processing techniques, this model helps in identifying the emotional tone of sentences, making it ideal for various applications in social media monitoring, customer feedback analysis, and more.
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## Acknowledgments
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We would like to thank the Hugging Face community for their support and contributions to the development of this model.
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