Create README.md

README.md

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+---
+language:
+- en
+---
+A question generation model trained on `alinet/balanced_qg` dataset.
+
+Example usage:
+
+```py
+from transformers import BartConfig, BartForConditionalGeneration, BartTokenizer
+
+model_name = "alinet/bart-base-balanced-qg"
+
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name) 
+
+def run_model(input_string, **generator_args):
+  input_ids = tokenizer.encode(input_string, return_tensors="pt")
+  res = model.generate(input_ids, **generator_args)
+  output = tokenizer.batch_decode(res, skip_special_tokens=True)
+  print(output)
+
+run_model("Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.", max_length=32, num_beams=4)
+# ['What is the Stanford Question Answering Dataset?']
+```