Text Classification
Transformers
PyTorch
Safetensors
English
roberta
argument-mining
opinion-mining
information-extraction
inference-extraction
Twitter
Instructions to use TomatenMarc/WRAP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomatenMarc/WRAP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TomatenMarc/WRAP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TomatenMarc/WRAP") model = AutoModelForSequenceClassification.from_pretrained("TomatenMarc/WRAP") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:a2568bc422fd62b7ef76c1f34250909f5d95411975d77008a51f75ebf180130a
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size 539637448
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