Token Classification
Transformers
Safetensors
Spanish
bert
ner
spanish
emergencies
ecu-911
Eval Results (legacy)
Instructions to use dannyLeo16/ner_model_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dannyLeo16/ner_model_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dannyLeo16/ner_model_bert_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dannyLeo16/ner_model_bert_base") model = AutoModelForTokenClassification.from_pretrained("dannyLeo16/ner_model_bert_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from dannyLeo16/ner_model_bert_base: direct link, hf CLI and curl.
- Browser
- Download file 730 kB
-
https://huggingface.co/dannyLeo16/ner_model_bert_base/resolve/main/tokenizer.json
- Command line
-
hf download hf://dannyLeo16/ner_model_bert_base/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/dannyLeo16/ner_model_bert_base/resolve/main/tokenizer.json
730 kB
File too large to display, you can check the raw version instead.