Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
language-identification
text-embeddings-inference
Instructions to use polyglot-tagger/multilabel-language-identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use polyglot-tagger/multilabel-language-identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="polyglot-tagger/multilabel-language-identification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("polyglot-tagger/multilabel-language-identification") model = AutoModelForSequenceClassification.from_pretrained("polyglot-tagger/multilabel-language-identification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from polyglot-tagger/multilabel-language-identification: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/polyglot-tagger/multilabel-language-identification/resolve/main/training_args.bin
- Command line
-
hf download hf://polyglot-tagger/multilabel-language-identification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/polyglot-tagger/multilabel-language-identification/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- d1db0ad348e04ded8771326b634505c32e114d6ebec11bc810193952f1d60cac
- Size of remote file:
- 5.2 kB
- SHA256:
- c58abd36bff753b4801af7c72bd4232a77a6af17c644afb347fc931f0c45cedd
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