Bert Base Uncased Snli is a text classification model hosted on Hugging Face. It consists of a BERT-base-uncased architecture that has been fine-tuned for natural language inference tasks on the SNLI dataset and produces three-class outputs corresponding to entailment, contradiction, or neutral relations between sentence pairs.
The model can be loaded and run through the Transformers library using either a high-level pipeline for text-classification or by directly instantiating an AutoTokenizer and an AutoModelForSequenceClassification. It supports execution on PyTorch and JAX runtimes and is distributed as part of the open repository maintained by TextAttack. Downloads of the model reached 67,700 in the most recent month reported.
No model card is present on the repository page, and the model is not deployed by any inference provider. It is provided for direct use in notebooks such as Google Colab or Kaggle as well as in local applications and custom inference setups. The repository is publicly accessible without charge.
Bert Base Uncased Snli sits in PulseGate's Other AI category. It focuses on determining whether a hypothesis is entailed by, contradicts, or is neutral to a given premise in natural language. It is built as an open-source project for developers. Bert Base Uncased Snli is open source under the Open Source license. It runs on the web and API.
It is developed by TextAttack. Key capabilities include Text Classification, Natural Language Inference, and BERT Model. It exposes integrations via a public API.
Latest indexed changes and source events
textattack/bert-base-uncased-snli verified by the PulseGate indexer
