Instructions to use Transducens/xlm-roberta-base-parallel-urls-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Transducens/xlm-roberta-base-parallel-urls-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Transducens/xlm-roberta-base-parallel-urls-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Transducens/xlm-roberta-base-parallel-urls-classifier") model = AutoModelForSequenceClassification.from_pretrained("Transducens/xlm-roberta-base-parallel-urls-classifier") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7c7beaac720d0aa7579702960afc51729bc5bf831eb824ec787c690515af70e
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size 1114568708
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