Text Classification
Transformers
PyTorch
Safetensors
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use Sociovestix/lenu_ES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sociovestix/lenu_ES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sociovestix/lenu_ES")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sociovestix/lenu_ES") model = AutoModelForSequenceClassification.from_pretrained("Sociovestix/lenu_ES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Licensing Information
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This model, which is trained on LEI data, is available under Creative Commons (CC0) license.
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See [gleif.org/en/about/open-data](https://gleif.org/en/about/open-data).
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# Licensing Information
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This model, which is trained on LEI data, is available under Creative Commons (CC0) license.
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See [gleif.org/en/about/open-data](https://gleif.org/en/about/open-data).
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# Recommendations
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Users should always consider the score of the suggested ELF Codes. For low score values it may be necessary to manually review the affected entities.
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