Token Classification
Transformers
Safetensors
English
modernbert
Generated from Trainer
named-entity-recognition
Eval Results (legacy)
Instructions to use MatteoFasulo/ModernBERT-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MatteoFasulo/ModernBERT-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MatteoFasulo/ModernBERT-base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MatteoFasulo/ModernBERT-base-NER") model = AutoModelForTokenClassification.from_pretrained("MatteoFasulo/ModernBERT-base-NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00b46465f479683dce8e46efb5690c34b8338bd6d324873a77c72bbda6eccca1
- Size of remote file:
- 4.73 kB
- SHA256:
- 28d029ac41b9ef2b9e91afb8198a7ec8a97ccc8d3f71a315983f3435bb9a9e38
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