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")# 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
Commit ·
1a182ba
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Parent(s): a5d0aa7
Librarian Bot: Update dataset YAML metadata for model
Browse filesThis is a pull request to add a dataset, [`papluca/language-identification`](https://huggingface.co/datasets/papluca/language-identification), to the metadata for your model (defined in the `YAML` block of your model's `README.md`).
The pull request was made by [librarian-bot](https://huggingface.co/librarian-bot) and used a combination of rules and/or machine learning to suggest this additional metadata.
If this suggestion is incorrect, feel free to close this pull request.
Librarian Bot was made by [@davanstrien](https://huggingface.co/davanstrien); feel free to get in touch with feedback.
README.md
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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license: mit
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tags:
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- generated_from_trainer
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datasets: papluca/language-identification
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metrics:
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- accuracy
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- f1
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