Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-bert-blame-concept 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-concept 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-concept")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-bert-blame-concept") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-bert-blame-concept") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac6fa79309342dd7551e346af74154a9a3c41d7c38553ce8f73357bcc8076c50
- Size of remote file:
- 443 MB
- SHA256:
- c41f9678df7a0ce56a25a3a39f2f9172097a7fe1806bde19632ae3f0f2137051
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