Token Classification
Transformers
PyTorch
Spanish
roberta
PyTorch
Transformers
Token Classification
roberta-base-bne
Instructions to use sdocio/es_trf_ner_cds_bne-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sdocio/es_trf_ner_cds_bne-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sdocio/es_trf_ner_cds_bne-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sdocio/es_trf_ner_cds_bne-base") model = AutoModelForTokenClassification.from_pretrained("sdocio/es_trf_ner_cds_bne-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sdocio/es_trf_ner_cds_bne-base: direct link, hf CLI and curl.
- Browser
- Download file 2.21 MB
-
https://huggingface.co/sdocio/es_trf_ner_cds_bne-base/resolve/main/tokenizer.json
- Command line
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hf download hf://sdocio/es_trf_ner_cds_bne-base/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/sdocio/es_trf_ner_cds_bne-base/resolve/main/tokenizer.json
2.21 MB
File too large to display, you can check the raw version instead.