Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use papluca/xlm-roberta-base-language-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use papluca/xlm-roberta-base-language-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="papluca/xlm-roberta-base-language-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("papluca/xlm-roberta-base-language-detection") model = AutoModelForSequenceClassification.from_pretrained("papluca/xlm-roberta-base-language-detection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#8
by librarian-bot - opened
README.md
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metrics:
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- accuracy
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- f1
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model-index:
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- name: xlm-roberta-base-language-detection
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results: []
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metrics:
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- accuracy
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- f1
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base_model: xlm-roberta-base
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model-index:
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- name: xlm-roberta-base-language-detection
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results: []
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