# XLM-RoBERTa for question answering in Indian languages
pre-trained XLM-Roberta with intermediate pre-training on SQUAD dataset (English) and fine tuning on Chaii dataset (Tamil, Hindi)

# How to use from the 🤗/transformers library

```
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
  
tokenizer = AutoTokenizer.from_pretrained("gokulkarthik/xlm-roberta-qa-chaii")

model = AutoModelForQuestionAnswering.from_pretrained("gokulkarthik/xlm-roberta-qa-chaii")
```
{"language": ["en", "ta", "hi"], "datasets": ["squad", "chaii"], "widget": [{"text": "\u0b85\u0bb2\u0bc1\u0bae\u0bbf\u0ba9\u0bbf\u0baf\u0ba4\u0bcd\u0ba4\u0bbf\u0ba9\u0bcd \u0b85\u0ba3\u0bc1 \u0b8e\u0ba3\u0bcd \u0b8e\u0ba9\u0bcd\u0ba9?", "context": "\u0b85\u0bb2\u0bc1\u0bae\u0bbf\u0ba9\u0bbf\u0baf\u0bae\u0bcd (\u0b86\u0b99\u0bcd\u0b95\u0bbf\u0bb2\u0bae\u0bcd: \u0b85\u0bb2\u0bc1\u0bae\u0bbf\u0ba9\u0bbf\u0baf\u0bae\u0bcd; \u0bb5\u0b9f \u0b85\u0bae\u0bc6\u0bb0\u0bbf\u0b95\u0bcd\u0b95 \u0b86\u0b99\u0bcd\u0b95\u0bbf\u0bb2\u0bae\u0bcd: Aluminum) \u0b92\u0bb0\u0bc1 \u0bb5\u0bc7\u0ba4\u0bbf\u0baf\u0bbf\u0baf\u0bb2\u0bcd \u0ba4\u0ba9\u0bbf\u0bae\u0bae\u0bcd \u0b86\u0b95\u0bc1\u0bae\u0bcd. \u0b87\u0ba4\u0ba9\u0bc1\u0b9f\u0bc8\u0baf \u0b85\u0ba3\u0bc1 \u0b8e\u0ba3\u0bcd 13 \u0b86\u0b95\u0bc1\u0bae\u0bcd. \u0b87\u0ba4\u0bc1 \u0baa\u0bc2\u0bae\u0bbf\u0baf\u0bbf\u0bb2\u0bcd \u0b85\u0ba4\u0bbf\u0b95\u0bae\u0bcd \u0b95\u0bbf\u0b9f\u0bc8\u0b95\u0bcd\u0b95\u0bc1\u0bae\u0bcd 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This number can vary depending on the physiological differences. For example, in a very small number of humans, an extra rib (neck) or an extra lower spinal cord is found. There are 22 bones in the human skull (excluding the ear tendons), which are divided into eight cranium bones and 14 facial bones. (Thick numbers indicate the numbers seen in the nearby picture.) Bones (8) 1 frontal bone (2) 3 temporal bone (2) 4 occipital bone (4) Sphinoid bone (14) 7 mandible (6) maxilla (2) palatine bone (2) 5 zygotic bone (9) 9 nasal bone (2) The sacral vertebrae (4 or 5), in adults, form the sacral vertebrae (3 to 5), in adults they form the valve."}]}
transformers pytorch xlm-roberta question-answering en ta hi dataset:squad dataset:chaii endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #question-answering #en #ta #hi #dataset-squad #dataset-chaii #endpoints_compatible #region-us 

# XLM-RoBERTa for question answering in Indian languages
pre-trained XLM-Roberta with intermediate pre-training on SQUAD dataset (English) and fine tuning on Chaii dataset (Tamil, Hindi)

# How to use from the /transformers library


# XLM-RoBERTa for question answering in Indian languages
pre-trained XLM-Roberta with intermediate pre-training on SQUAD dataset (English) and fine tuning on Chaii dataset (Tamil, Hindi) # How to use from the /transformers library
TAGS
#transformers #pytorch #xlm-roberta #question-answering #en #ta #hi #dataset-squad #dataset-chaii #endpoints_compatible #region-us 
 # XLM-RoBERTa for question answering in Indian languages
pre-trained XLM-Roberta with intermediate pre-training on SQUAD dataset (English) and fine tuning on Chaii dataset (Tamil, Hindi) # How to use from the /transformers library
passage: TAGS
#transformers #pytorch #xlm-roberta #question-answering #en #ta #hi #dataset-squad #dataset-chaii #endpoints_compatible #region-us 
# XLM-RoBERTa for question answering in Indian languages
pre-trained XLM-Roberta with intermediate pre-training on SQUAD dataset (English) and fine tuning on Chaii dataset (Tamil, Hindi)# How to use from the /transformers library