[Help] GPU with query answering
I want to figure out some way to get faster results from a QA model. I did some tests on google cloud with different GPUs and got some results, those tests was made with different GPUs and same CPU using this code:

```
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
from transformers.pipelines import pipeline

tokenizer = AutoTokenizer.from_pretrained("deepset/bert-large-uncased-whole-word-masking-squad2")
model = AutoModelForQuestionAnswering.from_pretrained("deepset/bert-large-uncased-whole-word-masking-squad2")
nlp_qa = pipeline('question-answering', model=model, tokenizer=tokenizer)
X = nlp_qa(context = text, question=queryy, topk = 3, device = 0, max_answer_len = 50)
```
Where context is just a long string and the question a simple query, and I got those results:

```
TESTE 1: **********
4 vCPUs 15Gb RAM 
NVIDIA TESLA P100X1
Tempo1: 1:45 min
Tempo2: 1:40 min
Tempo3: 1:45 min
***************
***************
TESTE 2: **********
4 vCPUs 15Gb RAM 
NVIDIA TESLA V100X1
Tempo1: 1:58 min
Tempo2: 1:58 min
Tempo3: 1:55 min
***************
***************
TESTE 3: **********
4 vCPUs 15Gb RAM 
NVIDIA TESLA K80X1
Tempo1: 2:06 min
Tempo2: 2:18 min
Tempo3: 2:20 min
***************
***************
TESTE 4: **********
4 vCPUs 15Gb RAM 
NVIDIA TESLA T4X1
Tempo1: 1:45 min
Tempo2: 1:50 min
Tempo3: 1:50 min
***************
***************
TESTE 5: **********
4 vCPUs 15Gb RAM 
NVIDIA NONE
Tempo1: 2:22 min
Tempo2: 1:57 min
Tempo3: 1:57 min
```

I want to know if I am  using GPU wrong, or is it normal to get almost same results with and without GPU on this set?.
Is there anyway to get faster results?
Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.
Could you ask your question on the [forum](https://discusss.huggingface.co) instead?

Thanks!