Zero-Shot Classification
Transformers
PyTorch
TensorFlow
Safetensors
xlm-roberta
text-classification
tensorflow
nli
natural-language-inference
Eval Results (legacy)
Instructions to use nahiar/zero-shot-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nahiar/zero-shot-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="nahiar/zero-shot-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nahiar/zero-shot-classification") model = AutoModelForSequenceClassification.from_pretrained("nahiar/zero-shot-classification") - Notebooks
- Google Colab
- Kaggle
Raihan Hidayatullah Djunaedi commited on
Commit ·
762e268
1
Parent(s): 2d694d9
Fix model card metadata: add required metrics section
Browse files
README.md
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dataset:
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name: XNLI
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type: xnli
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widget:
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- text: "За кого вы голосуете в 2020 году?"
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candidate_labels: "politique étrangère, Europe, élections, affaires, politique"
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dataset:
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name: XNLI
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type: xnli
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metrics:
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- type: accuracy
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value: 0.834
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name: Accuracy
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- type: f1
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value: 0.833
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name: F1 Score
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widget:
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- text: "За кого вы голосуете в 2020 году?"
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candidate_labels: "politique étrangère, Europe, élections, affaires, politique"
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