Instructions to use cjvt/roberta-en-hi-codemixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cjvt/roberta-en-hi-codemixed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cjvt/roberta-en-hi-codemixed")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cjvt/roberta-en-hi-codemixed") model = AutoModelForMaskedLM.from_pretrained("cjvt/roberta-en-hi-codemixed") - Notebooks
- Google Colab
- Kaggle
en-hi-codemixed
This is a masked language model, based on the CamemBERT model architecture. en-hi-codemixed model was trained from scratch on English, Hindi, and codemixed English-Hindi corpora for 40 epochs. The corpora used consists of primarily web crawled data, including codemixed tweets, and focuses on conversational language and covid-19 pandemic.
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