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distilbert-base-uncased-mnli

typeform

- Model Details - How to Get Started With the Model - Uses - Risks, Limitations and Biases - Training - Evaluation - Environmental Impact **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. **CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.**

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mobilebert-uncased-mnli

typeform

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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