DistilBERT base model (uncased) Table of Contents Model Details How to Get Started With the Model Uses Risks, Limitations and Biases Training Evaluation Environmental Impact Model Details Model Description: This is the uncased DistilBERT model fine tuned on Multi Genre Natural Language Inference (MNLI) dataset for the zero shot classification task. Developed by: The Typeform team. Model Type: Zero Shot Classification Language(s): English License: Unknown Parent Model: See the distilbert base uncased model for more information about the Distilled BERT base model. How to Get Started with the Model Uses This model can be used for text classification tasks. Risks, Limitations and Biases CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes. Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Training Training Data This model of DistilBERT uncased is pretrained on the Multi Genre Natural Language Inference (MultiNLI) corpus. It is a crowd sourced collection of 433k sentence pairs annotated with textual…
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