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:
- 5ba6f41a69a2f56c21be5ff9c6693763fd320989c4640089bdb14f3718addde1
- Size of remote file:
- 598 MB
- SHA256:
- 45bb8e419609e2c92de3755a24d4c37f3ac9e7f3dd2db7143acbc963ec474962
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