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:
- 404c1fb20a18ec02bbdabd1da6867e5ba3697b979a2a24b3c7ad976546572665
- Size of remote file:
- 17.1 MB
- SHA256:
- f2c509a525eb51aebb33fb59c24ee923c1d4c1db23c3ae81fe05ccf354084f7b
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