Checking that the LM actually trained 
I have trained a gpt2 from scratch with the way that is decribed in that post https://huggingface.co/blog/how-to-train  . 
Just in the step 4, where he checks if the trained model actually works, he uses from pipeline the 
"fill-mask" but that works only for models with  masked language modeling objective. 
Exists something similar i could use like "fill-mask" for my case?
Yes: simply `model.generate()` (not even a need for a Pipeline in that case)

cc @patrickvonplaten <|||||>I'd check if 'GPT2' works by sampling from a simple prompt. E.g.:

```
output = model.generate(tokenizer.encode('The president', return_tensors='pt'), do_sample=True)
tokenizer.decode(output[0])
```
<|||||>Thanks for clarifying!  I was about to consider sending a PR for a `GenerationPipeline` under `transformers.pipeline`.<|||||>#### I have a branch that implements a GenerationPipeline which already works for GPT models

The initial version of `GenerationPipeline` can be found in the branch's pipelines [module](https://github.com/enzoampil/transformers/blob/generation_pipeline/src/transformers/pipelines.py), where I've registered it to the `pipeline` function using `gpt2` as the default.

The implementation is based on the approach taken in [run_generation.py](https://github.com/huggingface/transformers/blob/master/examples/run_generation.py), which means the forward pass uses the `model.generate()` method explained by @julien-c and @patrickvonplaten  above.

So far, the code above works smoothly for `open-ai` and `gpt2`. 

Sample code:
```
# Pip install
# If you're using Google Colab, make sure to reset runtime after installing
!pip install -e git+git://github.com/enzoampil/transformers.git@generation_pipeline#egg=transformers

# Pipeline uses `gpt2` by default
from transformers import pipeline
gpt = pipeline('generation', num_return_sequences=1, length=40)
gpt("You look great")
# ['You look great, me!" he says. "There\'s nothing wrong with that, it\'s just I wanted a bit of attention so I had to go to work. I had to back down."\n']

```

However, the module still doesn't work with other language models like `xlm`, `xlnet`, and `transfo-xl`.

I will do a root cause analysis on this and will send a PR as soon as I get this to work on the rest of the language models that should work with `GenerationPipeline` (i.e. those runnable from `run_generation.py`).

For more details, you can check out this [colab notebook](https://colab.research.google.com/drive/1PHmYRpgzdMeSR68i4w5tPfUjlv0npCQz), which shows the gpt models working so far, and the rest of the models not working in the later sections.<|||||>#### [UPDATE] The issues above have been resolved and I'm in the process of sending a PR.

Google Colab tutorial [here](https://colab.research.google.com/drive/1PHmYRpgzdMeSR68i4w5tPfUjlv0npCQz) for running `GenerationPipeline` for the following LM models:
1. OpenAI GPT
2. OpenAI GPT-2
3. Transformer-XL
4. XML
5. XLNet
6. T5
7. CTRL
<|||||>You're PR looks very nice so far :-) I will take a look early next week!<|||||>Thanks!<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
