Text Classification
Transformers
PyTorch
xlm-roberta
classification
Generated from Trainer
text-embeddings-inference
Instructions to use Atram11/ClassificationLanguage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atram11/ClassificationLanguage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Atram11/ClassificationLanguage")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Atram11/ClassificationLanguage") model = AutoModelForSequenceClassification.from_pretrained("Atram11/ClassificationLanguage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e01c971bea83496d205c2b3534840abe3a83633f3cc842fdc39dde5fdb4bd83
- Size of remote file:
- 4.03 kB
- SHA256:
- a5b9f19e810f1bcd9659d6c169371e6f859e7e662db29b0ba5fd8bfd360a715f
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