Instructions to use yigitkucuk/Sentimentale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yigitkucuk/Sentimentale with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yigitkucuk/Sentimentale")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yigitkucuk/Sentimentale") model = AutoModelForSequenceClassification.from_pretrained("yigitkucuk/Sentimentale") - Notebooks
- Google Colab
- Kaggle
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README.md
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A Multi-Class Text-Classification Model that Evaluates the Sentiment in Poetic Text Prompts.
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A Multi-Class Text-Classification Model that Evaluates the Sentiment in Poetic Text Prompts.
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- positive
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- mixed
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- no_impact
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- negative
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