Token Classification
Transformers
Safetensors
English
bert
ner
named-entity-recognition
text-classification
sequence-labeling
transformer
nlp
pretrained-model
dataset-finetuning
deep-learning
huggingface
conll2025
real-time-inference
efficient-nlp
high-accuracy
gpu-optimized
chatbot
information-extraction
search-enhancement
knowledge-graph
legal-nlp
medical-nlp
financial-nlp
Instructions to use boltuix/NeuroBERT-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boltuix/NeuroBERT-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="boltuix/NeuroBERT-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("boltuix/NeuroBERT-NER") model = AutoModelForTokenClassification.from_pretrained("boltuix/NeuroBERT-NER") - Inference
- Notebooks
- Google Colab
- Kaggle