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:
- 34411b085d553c85329cee1cffb23a1311fdbe8a37212c7737d683dc9d8cfb90
- Size of remote file:
- 443 MB
- SHA256:
- 5236b50d8eba10a373e910867ec075c3de746d3c3212945384998750c0dd1308
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