Text Classification
Transformers
PyTorch
TensorBoard
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use responsibility-framing/predict-perception-xlmr-focus-object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use responsibility-framing/predict-perception-xlmr-focus-object with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="responsibility-framing/predict-perception-xlmr-focus-object")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("responsibility-framing/predict-perception-xlmr-focus-object") model = AutoModelForSequenceClassification.from_pretrained("responsibility-framing/predict-perception-xlmr-focus-object") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97f32a5d8dae45e667bff1dff57c43044aa014074103da75f58e5bee5f7740cc
- Size of remote file:
- 1.11 GB
- SHA256:
- e5bd94f6e9311fd8717fd72fc69cf7138cfe1f47ca50b74dcade9458119a5df4
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