Instructions to use LocalDoc/sentiment_analysis_azerbaijani with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LocalDoc/sentiment_analysis_azerbaijani with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LocalDoc/sentiment_analysis_azerbaijani")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LocalDoc/sentiment_analysis_azerbaijani") model = AutoModelForSequenceClassification.from_pretrained("LocalDoc/sentiment_analysis_azerbaijani") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- analysis
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- azerbaijani
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widget:
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# Sentiment Analysis Model for Azerbaijani Text
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This repository hosts a fine-tuned XLM-RoBERTa model for sentiment analysis on Azerbaijani text. The model is capable of classifying text into three categories: negative, neutral, and positive.
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- analysis
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- azerbaijani
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widget:
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- text: Bu mənim xoşuma gəlir
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datasets:
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- LocalDoc/sentiments_dataset_azerbaijani
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# Sentiment Analysis Model for Azerbaijani Text
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This repository hosts a fine-tuned XLM-RoBERTa model for sentiment analysis on Azerbaijani text. The model is capable of classifying text into three categories: negative, neutral, and positive.
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