Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use Defensa2025/C3ROBERTA8020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Defensa2025/C3ROBERTA8020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Defensa2025/C3ROBERTA8020")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Defensa2025/C3ROBERTA8020") model = AutoModelForSequenceClassification.from_pretrained("Defensa2025/C3ROBERTA8020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- adb6fa49cf77d246bb8fd05305039961791c22c07eb88d46604bd5304e80c44f
- Size of remote file:
- 17.1 MB
- SHA256:
- 80eedf428dfd0ae49717c89c8b9054e08410707d981a9a68ca6cead79ae181c5
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