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- "Hello"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language: multilingual
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+ tags:
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+ - text-classification
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+ - pytorch
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+ - nli
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+ - xnli
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+ - de
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+ datasets:
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+ - xnli
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+
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+ pipeline_tag: zero-shot-classification
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+
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+ ---
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+
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+ # German Zeroshot
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+
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+ ## Model Description
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+
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+ This model has [GBERT Large](https://huggingface.co/deepset/gbert-large) as base model and fine-tuned it on xnli de dataset
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+
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+ #### Zero-shot classification pipeline
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+
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+ ```python
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+ from transformers import pipeline
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+ classifier = pipeline("zero-shot-classification",
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+ model="Sahajtomar/German_Zeroshot")
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+
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+ # we will classify the Russian translation of, "Who are you voting for in 2020?"
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+ sequence = "Letzte Woche gab es einen Selbstmord in einer nahe gelegenen kolonie"
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+ candidate_labels = ["Verbrechen","Tragödie","Stehlen"]
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+ hypothesis_template = "In deisem geht es um {}." ## Since monolingual model,its sensitive to hypothesis template. This can be experimented
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+
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+ classifier(sequence, candidate_labels, hypothesis_template=hypothesis_template)
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+ # {'labels': ['politics', 'Europe', 'public health'],
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+ # 'scores': [0.9048484563827515, 0.05722189322113991, 0.03792969882488251],
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+ # 'sequence': 'За кого вы голосуете в 2020 году?'}
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+ ```
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+
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+ The default hypothesis template is the English, `This text is {}`. If you are working strictly within one language, it
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+ may be worthwhile to translate this to the language you are working with:
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+
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+ ```python
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+ sequence_to_classify = "¿A quién vas a votar en 2020?"
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+ candidate_labels = ["Europa", "salud pública", "política"]
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+ hypothesis_template = "Este ejemplo es {}."
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+ classifier(sequence_to_classify, candidate_labels, hypothesis_template=hypothesis_template)
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+ """{'labels': ['Tragödie', 'Verbrechen', 'Stehlen'],
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+ 'scores': [0.8328856854438782, 0.10494536352157593, 0.06316883927583696],
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+ 'sequence': 'Letzte Woche gab es einen Selbstmord in einer nahe gelegenen Kolonie'}"""
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+ ```