Text Classification
Transformers
PyTorch
English
roberta
classification
framing
MediaFrames
argument classification
multilabel
RoBERTa-base
Instructions to use pheinisch/MediaFrame-Roberta-recall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pheinisch/MediaFrame-Roberta-recall with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pheinisch/MediaFrame-Roberta-recall")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pheinisch/MediaFrame-Roberta-recall") model = AutoModelForSequenceClassification.from_pretrained("pheinisch/MediaFrame-Roberta-recall") - 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 sha256:50afef8995cb1e5dafe916e7d7ef0e3b5331caba4125bf31a7c3998548d5c9ce
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size 498652812
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