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
add model
Browse files- config.json +1 -1
- tf_model.h5 +3 -0
config.json
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{
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"_name_or_path": "
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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{
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"_name_or_path": "papluca/xlm-roberta-base-language-detection",
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"architectures": [
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"XLMRobertaForSequenceClassification"
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],
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:d6417044a1451c9a5fd302579ee5d39bae3831b0cd57bd008b61e79d33156f6e
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size 1112525696
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