metadata
base_model: cross-encoder/nli-deberta-v3-xsmall
library_name: transformers.js
license: apache-2.0
language: en
pipeline_tag: zero-shot-classification
tags:
- onnx
- deberta-v2
- text-classification
- zero-shot-classification
- nli
- schift
- transformers.js
datasets:
- nyu-mll/multi_nli
- stanfordnlp/snli
schift-nli
ONNX-quantized DeBERTa-v3-xsmall for Natural Language Inference, optimized for Dot local inference.
- Base model: cross-encoder/nli-deberta-v3-xsmall
- ONNX source: Xenova/nli-deberta-v3-xsmall
- Parameters: 70.8M
- Labels: entailment, contradiction, neutral
- Use case: Intent routing, polarity detection, document pair classification
Usage in Dot
Loaded automatically by Dot's local NLI classifier. No manual setup needed.
Usage with Transformers.js
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('text-classification', 'schift-io/schift-nli', {
quantized: true,
});
const result = await classifier(
{ text: 'A man is eating pizza', text_pair: 'A man is eating food' },
{ top_k: 3 }
);
// [{ label: 'entailment', score: 0.97 }, ...]
License
Apache 2.0 (inherited from base model)