Text Classification
Transformers
PyTorch
English
roberta
text
stance
Eval Results (legacy)
text-embeddings-inference
Instructions to use eevvgg/Stance-Tw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eevvgg/Stance-Tw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eevvgg/Stance-Tw")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eevvgg/Stance-Tw") model = AutoModelForSequenceClassification.from_pretrained("eevvgg/Stance-Tw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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del cls report from readme
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up examples
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up readme corpus size
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up readme Stance-Tw
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tne mention model card
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up model card stance
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add colab file to model card
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naming model card
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create model card 2nd version
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senti - eth labels config
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del trainer_state.json 1st version
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2nd version push
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del sentencepiece.bpe.model
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up config labels
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1st push
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initial commit
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