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
File size: 129 Bytes
9791534 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c9a9d7a58bc9223dee1d333461ebe1123ca065bf8f9aa6bbd0e7f5bb70632e31
size 4600
|