Instructions to use elozano/tweet_sentiment_eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elozano/tweet_sentiment_eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elozano/tweet_sentiment_eval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elozano/tweet_sentiment_eval") model = AutoModelForSequenceClassification.from_pretrained("elozano/tweet_sentiment_eval") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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datasets:
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- tweet_eval
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language: en
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---
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datasets:
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- tweet_eval
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language: en
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widget:
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- text: "I love summer!"
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example_title: "Positive"
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- text: "Does anyone want to play?"
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example_title: "Neutral"
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- text: "This movie is just awful! 😫"
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example_title: "Negative"
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---
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