Text Classification
Transformers
TensorFlow
xlm-roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use hyperonym/barba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyperonym/barba with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hyperonym/barba")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hyperonym/barba") model = AutoModelForSequenceClassification.from_pretrained("hyperonym/barba", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Barba
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Barba is a multilingual natural language inference model for textual entailment and zero-shot text classification
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### Framework versions
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# Barba
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Barba is a multilingual [natural language inference](http://nlpprogress.com/english/natural_language_inference.html) model for [textual entailment](https://en.wikipedia.org/wiki/Textual_entailment) and [zero-shot text classification](https://joeddav.github.io/blog/2020/05/29/ZSL.html#Classification-as-Natural-Language-Inference), available as an end-to-end service through TensorFlow Serving. Based on [XLM-RoBERTa](https://arxiv.org/abs/1911.02116), it is trained on selected subsets of publicly available English ([GLUE](https://huggingface.co/datasets/glue)), Chinese ([CLUE](https://huggingface.co/datasets/clue)), Japanese ([JGLUE](https://huggingface.co/datasets/shunk031/JGLUE)), Korean ([KLUE](https://huggingface.co/datasets/klue)) datasets, as well as other private datasets.
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GitHub: https://github.com/hyperonym/barba
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### Framework versions
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