Token Classification
Transformers
Safetensors
English
roberta
ner
named-entity-recognition
Eval Results (legacy)
Instructions to use jayant-yadav/roberta-base-multinerd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayant-yadav/roberta-base-multinerd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jayant-yadav/roberta-base-multinerd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jayant-yadav/roberta-base-multinerd") model = AutoModelForTokenClassification.from_pretrained("jayant-yadav/roberta-base-multinerd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 47c0905
added lang info in metadata
Browse files
README.md
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type: Babelscape/multinerd
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name: MultiNERD
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split: test
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revision: 2814b78e7af4b5a1f1886fe7ad49632de4d9dd25
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metrics:
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- type: f1
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type: Babelscape/multinerd
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name: MultiNERD
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split: test
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lang: en
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revision: 2814b78e7af4b5a1f1886fe7ad49632de4d9dd25
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metrics:
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- type: f1
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