invalid multinomial distribution (with replacement=False, not enough non-negative category to sample)
When using "sshleifer/distilbart-cnn-6-6" & do_sample the below code errors out, meanwhile the same code works for "sshleifer/distilbart-xsum-6-6". Am I missing something really obvious here? Thanks for any help!

Tranformers: 4.5.1

````
from transformers import (
    AutoModelForSeq2SeqLM, 
    AutoTokenizer
  )

model_name = "sshleifer/distilbart-cnn-6-6"
#model_name = "sshleifer/distilbart-xsum-6-6"
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

text = "New York City (NYC), often simply called New York, is the most populous city in the United States"
input_ids = tokenizer.encode(text, return_tensors='pt')

sample_outputs = model.generate(input_ids, 
                                num_beams=3,
                                do_sample=True
                                )
sample_outputs
````
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.<|||||>i have the same exact problem when i use `do_sample=True` can you re-open this issue?<|||||>Maybe @gante has an idea!<|||||>Hi there @Muennighoff @zeke-john 👋 

I've run the script above for both models on `v4.5.1` (and on `v4.22.dev0`) and it works with no problems -- you can see a colab [here](https://colab.research.google.com/drive/1bg7v0mxZbFxJTjj28AriYBeERsAN264E?usp=sharing).

A potential cause for errors may be GPU memory -- generation with `num_beams` is memory intensive. Let me know if you have more details about your problem :)