Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-bert-blame-object 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-object 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-object")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-bert-blame-object") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-bert-blame-object", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26f53d3d5e83f4401195cc065ca5c81638359df89024eb8be6666583475c0195
- Size of remote file:
- 443 MB
- SHA256:
- 390a06471e7400a95fa3fb32813c5366fb974b86781cbfd60081a197dbeef6d7
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