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- ---
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- library_name: transformers
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- license: apache-2.0
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- ---
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- ```
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  base_model: distilbert/distilbert-base-multilingual-cased
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- language: multilingual
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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  pipeline_tag: text-classification
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  tags:
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  - product-reviews
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  - brand-monitoring
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  widget:
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- - text: "I absolutely loved this movie! The acting was superb and the plot was engaging."
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- example_title: Very Positive Review (English)
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- - text: "我讨厌这种无休止的争吵。"
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- example_title: Very Negative Review (Chinese)
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- - text: "El producto funciona como se espera. Nada especial, pero cumple con su función."
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- example_title: Neutral Review (Spanish)
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- - text: "هذا الكتاب غير حياتي! لقد تعلمت الكثير منه."
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- example_title: Very Positive Review (Arabic)
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- - text: разочарован покупкой, это не так хорошо, как я надеялся."
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- example_title: Negative Review (Russian)
 
 
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  inference:
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  parameters:
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  temperature: 1
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- ```
 
 
 
 
 
 
 
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  # 🚀 distilbert-based Multilingual Sentiment Classification Model
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+ ---
 
 
 
 
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  base_model: distilbert/distilbert-base-multilingual-cased
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+ language:
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+ - en
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+ - zh
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+ - es
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+ - hi
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+ - ar
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+ - bn
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+ - pt
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+ - ru
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+ - ja
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+ - de
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+ - ms
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+ - te
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+ - vi
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+ - ko
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+ - fr
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+ - tr
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+ - it
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+ - pl
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+ - uk
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+ - tl
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+ - nl
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+ - gsw
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+
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  license: apache-2.0
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  pipeline_tag: text-classification
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  tags:
 
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  - product-reviews
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  - brand-monitoring
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  widget:
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+ - text: >-
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+ I absolutely loved this movie! The acting was superb and the plot was
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+ engaging.
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+ example_title: Very Positive Review
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+ - text: The service at this restaurant was terrible. I'll never go back.
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+ example_title: Very Negative Review
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+ - text: The product works as expected. Nothing special, but it gets the job done.
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+ example_title: Neutral Review
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+ - text: I'm somewhat disappointed with my purchase. It's not as good as I hoped.
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+ example_title: Negative Review
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+ - text: This book changed my life! I couldn't put it down and learned so much.
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+ example_title: Very Positive Review
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  inference:
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  parameters:
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  temperature: 1
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+ ---
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+
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+ "Chinese (中文)", "Spanish (Español)", "Hindi (हिन्दी)", "Arabic (العربية)",
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+ "Bengali (বাংলা)", "Portuguese (Português)", "Russian (Русский)", "Japanese (日本語)",
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+ "German (Deutsch)", "Malay (Bahasa Melayu)", "Telugu (తెలుగు)",
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+ "Vietnamese (Tiếng Việt)", "Korean (한국어)", "French (Français)", "Turkish (Türkçe)",
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+ "Italian (Italiano)", "Polish (Polski)", "Ukrainian (Українська)",
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+ "Tagalog", "Dutch (Nederlands)", "Swiss German (Schweizerdeutsch)"
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  # 🚀 distilbert-based Multilingual Sentiment Classification Model
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