Create README.md

README.md

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+Next word generator trained on questions. Receives partial questions and tries to predict the next word.
+Example use: 
+
+```python
+from transformers import T5Config, T5ForConditionalGeneration, T5Tokenizer
+
+model_name = "allenai/t5-small-next-word-generator-qoogle"
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.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)
+    return output
+
+
+run_model("Which")
+run_model("Which two")
+run_model("Which two counties")
+run_model("Which two counties are")
+run_model("Which two counties are the")
+run_model("Which two counties are the biggest")
+run_model("Which two counties are the biggest economic")
+run_model("Which two counties are the biggest economic powers")
+
+```
+which should result in the following:
+```
+['one']
+['statements']
+['are']
+['in']
+['most']
+['in']
+['zones']
+['of']
+``` 
+