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:
- ec0d5ef25df306de84de6700d8cf1f37812584a99076f59d8f71926ef79b4efd
- Size of remote file:
- 712 MB
- SHA256:
- 93a98affc3198c76d2f7b8a492dcc048631557d1a3ce11be146bc74e40b1f1e5
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