Sample usage: 
```python 
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("danyaljj/gpt2_question_answering_squad2")

input_ids = tokenizer.encode("There are two apples on the counter. Q: How many apples? A:", return_tensors="pt")
outputs = model.generate(input_ids)
print("Generated:", tokenizer.decode(outputs[0], skip_special_tokens=True))
```

Which should produce this: 
```
Generated: There are two apples on the counter. Q: How many apples? A: two
```
{}
transformers pytorch gpt2 text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

Sample usage: 


Which should produce this: 

TAGS
#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

TAGS
#transformers #pytorch #gpt2 #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
