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:
- 2d347ebee0cf93a7270b2443257f6b7fd80315ac9fc370f9c0cc653b61b2acb7
- Size of remote file:
- 4.6 kB
- SHA256:
- c9a9d7a58bc9223dee1d333461ebe1123ca065bf8f9aa6bbd0e7f5bb70632e31
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