Instructions to use orai-nlp/ElhBERTeu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orai-nlp/ElhBERTeu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="orai-nlp/ElhBERTeu")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("orai-nlp/ElhBERTeu") model = AutoModel.from_pretrained("orai-nlp/ElhBERTeu") - Inference
- Notebooks
- Google Colab
- Kaggle
Gorka Urbizu Garmendia commited on
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README.md
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@@ -27,11 +27,11 @@ ElhBERTeu was trained following the design decisions for [BERTeus](https://huggi
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The model has been evaluated on the recently created BasqueGLUE NLU benchmark:
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| Model | AVG | NERC
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| | | F1
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| BERTeus | 73.23 | 81.92
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| ElhBERTeu | **73.71** | 82.30 | 82.24 |
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If you use this model, please cite the following paper:
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The model has been evaluated on the recently created BasqueGLUE NLU benchmark:
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| Model | AVG | NERC | F_intent | F_slot | BHTC | BEC | Vaxx | QNLI | WiC | coref |
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| | | F1 | F1 | F1 | F1 | F1 | MF1 | acc | acc | acc |
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| BERTeus | 73.23 | 81.92 | **82.52** | 74.34 |**78.26**| 69.43 | 59.30 |**74.26**| 70.71 |**68.31**|
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| ElhBERTeu | **73.71** | **82.30** | 82.24 |**75.64**| 78.05 |**69.89**|**63.81**| 73.84 |**71.71**| 65.93 |
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If you use this model, please cite the following paper:
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