This project features an Emotion Detector powered by the RoBERTa model for sentiment analysis. The model is trained to predict underlying emotions in text. Users can explore the capabilities of this model through a demo or download the pre-trained model state dict for further tuning.
Visit our online demo to experience the Emotion Detector in action:
For users interested in fine-tuning the model or using it for their specific applications, the pre-trained model state dict can be downloaded from the following Hugging Face model hub link:
Download Deployment Files and RoBERTa Model State Dict
- Download the RoBERTa model state dict from the provided link.
- Integrate the state dict into your project for fine-tuning.
- Follow the appropriate fine-tuning procedures for your specific use case.
The RoBERTa model used in this project has been fine-tuned for sentiment analysis tasks. It is based on the Transformer architecture and has shown high performance in understanding and analyzing natural language text.