| # Telugu Question-Answering model trained on Tydiqa dataset from Google | |
| #### How to use | |
| Use the below script from your python terminal as the web interface for inference has few encoding issues for Telugu | |
| ```python | |
| from transformers.pipelines import pipeline, AutoModelForQuestionAnswering, AutoTokenizer | |
| model = AutoModelForQuestionAnswering.from_pretrained(model_name) | |
| tokenizer = AutoTokenizer.from_pretrained("kuppuluri/telugu_bertu_tydiqa", | |
| clean_text=False, | |
| handle_chinese_chars=False, | |
| strip_accents=False, | |
| wordpieces_prefix='##') | |
| nlp = pipeline('question-answering', model=model, tokenizer=tokenizer) | |
| result = nlp({'question': question, 'context': context}) | |
| ``` | |
| ## Training data | |
| I used Tydiqa Telugu data from Google https://github.com/google-research-datasets/tydiqa | |
| PS: If you find my model useful, I would appreciate a note from you as it would encourage me to continue improving it and also add new models. | |