Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-bert-blame-victim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use responsibility-framing/predict-perception-bert-blame-victim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="responsibility-framing/predict-perception-bert-blame-victim")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-bert-blame-victim") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-bert-blame-victim") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9f695072ebfdbb63513f1dab9a9b456d7984ae1ac9abb9da343ae3b2cf3f7f3
- Size of remote file:
- 3.12 kB
- SHA256:
- d2bf95067847e6260c0edd8c780b06a3b52e3181cf648fde23837e103a4dfe12
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