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") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- generated_from_keras_callback
model-index:
- name: barba
results: []
license: mit
datasets:
- snli
- glue
- clue
- shunk031/JGLUE
- klue
language:
- en
- zh
- ja
- ko
Barba
Barba is a multilingual natural language inference model for textual entailment and zero-shot text classification, available as an end-to-end service through TensorFlow Serving. Based on XLM-RoBERTa, it is trained on selected subsets of publicly available English (GLUE), Chinese (CLUE), Japanese (JGLUE), Korean (KLUE) datasets, as well as other private datasets.
GitHub: https://github.com/hyperonym/barba
Framework versions
- Transformers 4.28.1
- TensorFlow 2.11.1
- Datasets 2.11.0
- Tokenizers 0.13.3