Token Classification
Transformers
PyTorch
JAX
Safetensors
Hindi
English
multilingual
bert
codeswitching
hindi-english
ner
Instructions to use sagorsarker/codeswitch-hineng-ner-lince with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagorsarker/codeswitch-hineng-ner-lince with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sagorsarker/codeswitch-hineng-ner-lince")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince") model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4230787ab53d63f289fae8084a739ff00300fc58ba89c4344fd2bc61dc417235
- Size of remote file:
- 1.52 kB
- SHA256:
- 145cb27dee790a8d9024b347ef552487688ed09efbc679701e5d00228fc0c2cb
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