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distilbert-base-uncased-go-emotions-onnx

Cohee

This model is distilled from the zero-shot classification pipeline on the unlabeled GoEmotions dataset using this script. It was trained with mixed precision for 10 epochs and otherwise used the default script arguments. The model can be used like any other model trained on GoEmotions, but will likely not perform as well as a model trained with full supervision. It is primarily intended as a demo of how an expensive NLI-based zero-shot model can be distilled to a more efficient student, allowing a classifier to be trained with only unlabeled data. Note that although the GoEmotions dataset allow multiple labels per instance, the teacher used single-label classification to create psuedo-labels.

Text analysis

Input Text→ Output Text

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jina-embeddings-v2-base-en

Cohee

https://huggingface.co/jinaai/jina-embeddings-v2-base-en with ONNX weights to be compatible with Transformers.js.

Embeddings & similarity

Input Text→ Output Embedding

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Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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