

TITLE
Inference/prediction ValueError using BART

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### System Info

```shell
- `transformers` version: 4.18.0
- Platform: Linux-4.19.0-19-cloud-amd64-x86_64-with-debian-10.12
- Python version: 3.7.12
- Huggingface_hub version: 0.5.1
- PyTorch version (GPU?): 1.11.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
```


### Who can help?

@patil-suraj

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

```python
from transformers import BartForConditionalGeneration, BartTokenizerFast
from transformers import Seq2SeqTrainer, Seq2SeqTrainingArguments
from datasets import load_dataset

raw_dataset = load_dataset(path='parquet', data_files={
    'train': ['2021_1.parquet', '2021_2.parquet', '2021_3.parquet'], 
    'test': ['2021_4.parquet'
]})

model = BartForConditionalGeneration.from_pretrained("bart_nl_sum_17-04_15-50-23/checkpoints/checkpoint-10000")
tokenizer = BartTokenizerFast.from_pretrained("bart_nl_tiny_tz")

model_inputs = tokenizer(raw_dataset['train'][2]['description'], max_length=1024, return_tensors='pt', truncation=True) # padding=max_length

model_outputs = model.generate(
    inputs=model_inputs["input_ids"], 
    max_length=150, 
    min_length=40, 
    length_penalty=2.0, 
    num_beams=4, 
    early_stopping=True
)

print(tokenizer.decode(model_outputs[0]))
```

```python
Traceback (most recent call last):
  File "legalsum_inf.py", line 22, in <module>
    early_stopping=True
  File "/opt/conda/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/transformers/generation_utils.py", line 1325, in generate
    **model_kwargs,
  File "/opt/conda/lib/python3.7/site-packages/transformers/generation_utils.py", line 2162, in beam_search
    output_hidden_states=output_hidden_states,
  File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/transformers/models/bart/modeling_bart.py", line 1363, in forward
    return_dict=return_dict,
  File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/transformers/models/bart/modeling_bart.py", line 1224, in forward
    return_dict=return_dict,
  File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/transformers/models/bart/modeling_bart.py", line 793, in forward
    raise ValueError("You have to specify either input_ids or inputs_embeds")
ValueError: You have to specify either input_ids or inputs_embeds
```

### Expected behavior

```shell
I tried to summarize a text from my dataset using a custom fine-tuned BART model. To this end I followed the pytorch example listed at https://huggingface.co/docs/transformers/task_summary#summarization

This is the code that was used and the error that was shown. Any ideas what could be the problem here?
```
