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  # Text Classification GoEmotions
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- This model is a fined-tuned version of [nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset using [tasinho/text-classification-goemotions](https://huggingface.co/tasinhoque/text-classification-goemotions) as teacher model.
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  The quantized version in ONNX format can be found [here](https://huggingface.co/minuva/MiniLMv2-goemotions-v2-onnx)
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  # Load the Model
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  # Deployment
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- Check [our repository](https://github.com/minuva/emotion-prediction-serverless) to see how to easily deploy this (quantized) model in a serverless environment with fast CPU inference and light resource utilization.
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  # Text Classification GoEmotions
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+ This model is a fined-tuned version of [MiniLMv2-L6-H384](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset.
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  The quantized version in ONNX format can be found [here](https://huggingface.co/minuva/MiniLMv2-goemotions-v2-onnx)
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  # Load the Model
 
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  # Deployment
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+ Check out our [fast-nlp-text-emotion repository](https://github.com/minuva/fast-nlp-text-emotion) for a FastAPI based server to easily deploy this model on CPU devices.
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