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:
- da153d7c2056cccee6b817c158c0ae23bc31a00b13247b7ccd90cec466832f97
- Size of remote file:
- 3.12 kB
- SHA256:
- 0e538b5825faa476d1cd0b09d1c4e8418c268c9625878997ba584802ad4ea5d5
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