Model: nahiar/zero-shot-classification
Author: nahiar
Pipeline: zero-shot-classification
Library: transformers
Tags: transformers, pytorch, tf, safetensors, xlm-roberta, text-classification, tensorflow, zero-shot-classification, multilingual, nli, natural-language-inference, en, fr, es, de, el, bg, ru, tr, ar, vi, th, zh, hi, sw, ur, dataset:multi_nli, dataset:xnli, arxiv:1911.02116, license:mit, model-index, endpoints_compatible, region:us
Card metadata: language: multilingual, en, fr, es, de, el, bg, ru, tr, ar, vi, th, zh, hi, sw, ur
tags: text-classification, pytorch, tensorflow, zero-shot-classification, xlm-roberta, multilingual, nli, natural-language-inference
datasets: multi_nli, xnli
license: mit
pipeline_tag: zero-shot-classification
library_name: transformers
model-index: name: xlm-roberta-large-xnli
results: task: type: zero-shot-classification
name: Zero-Shot Classification
dataset: name: XNLI
type: xnli
metrics: type: accuracy
value: 0.834
name: Accuracy
verified: no, type: f1
value: 0.833
name: F1 Score
verified: no
widget: text: За кого вы голосуете в 2020 году?
candidate_labels: politique étrangère, Europe, élections, affaires, politique
multi_class: yes
example_title: Russian Political Classification, text: لمن تصوت في 2020؟
candidate_labels: السياسة الخارجية, أوروبا, الانتخابات, الأعمال, السياسة
multi_class: yes
example_title: Arabic Political Classification, text: 2020'de kime oy vereceksiniz?
candidate_labels: dış politika, Avrupa, seçimler, ticaret, siyaset
multi_class: yes
example_title: Turkish Political Classification, text: I love this movie
candidate_labels: positive, negative, neutral
multi_class: no
example_title: English Sentiment Analysis
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Created: 2025-07-08 13:42:31