How to accelerate the inference speed when using pipeline
> transformers version: 4.6.0.dev0
> torch version:1.8.1+cu102

I am using the simple API - pipeline, to do inference, where the input are tens of thousands of sentences.

```
nlp  = pipeline("text-generation", model= 'gpt2', device=0, return_full_text=False)
results = nlp(df_train['content'].tolist(), max_length=250, do_sample=True, top_p=0.9, top_k=0, \
                    repetition_penalty=1, num_return_sequences=64)
```
take the generation, for instance, I want to generate new synthesized samples from each sentence from the df_train.
The codes work well, but it is not fast enough. I mean the GPU usage is just 76% ~ 85%.
Is there any trick or parameters I can tune to speed up ?

Another question is that how can I eliminate the info:

> Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.




This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.<|||||>Hi @yananchen1989 did you get a solution yet