Text Classification
Transformers
Safetensors
bert
politics
twitter
tweets
issues
text-embeddings-inference
Instructions to use z-dickson/issue_classification_tweets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use z-dickson/issue_classification_tweets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="z-dickson/issue_classification_tweets")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("z-dickson/issue_classification_tweets") model = AutoModelForSequenceClassification.from_pretrained("z-dickson/issue_classification_tweets") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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license: mit
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This model classified politicians' tweets in English according to nine issues:
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license: mit
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tags:
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- politics
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- twitter
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- tweets
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- issues
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This model classified politicians' tweets in English according to nine issues:
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