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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93b5ac2d3676f531dd628ef0d0ad0b180ef75772f7fee29dc3e8d4785b43e538
- Size of remote file:
- 1.06 kB
- SHA256:
- c0acd1dd8634f9eb82171400dc990fc3f5742a8f7c08cbc9f0c189754ac18b98
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