word_ids method is not available on fast tokenizers when using "prepare_for_model"
Tokenizer: RoBERTa

```
hf_tokenizer = AutoTokenizer.from_pretrained("roberta-base")
hf_tokenizer.is_fast # = True

```
```
inputs = hf_tokenizer("This is a test")
print(inputs.word_ids())
input_ids = inputs["input_ids"]
```
Returns: `[None, 0, 1, 2, 3, None]`

```
inputs2 = hf_tokenizer.prepare_for_model(input_ids)
print(inputs2.word_ids())
```
Returns this error:
~/miniconda3/envs/blurr/lib/python3.9/site-packages/transformers/tokenization_utils_base.py in word_ids(self, batch_index)
    351         """
    352         if not self._encodings:
--> 353             raise ValueError("word_ids() is not available when using Python-based tokenizers")
    354         return self._encodings[batch_index].word_ids
    355 

ValueError: word_ids() is not available when using Python-based tokenizers

**Expected result**
Both approaches should return `[None, 0, 1, 2, 3, None]`

Hi,

The `prepare_for_model` is not a user-facing method, it's recommended to just call the tokenizer (as in your first code snippet). The `prepare_for_model` method does not set the `_encodings` field of `BatchEncoding` (this is only done in the `_encode_plus` and `_batch_encode_plus` methods of `tokenization_utils_fast.py` (as seen [here](https://github.com/huggingface/transformers/blob/2e9af294940083915ccb2740a7c8d5b154194f15/src/transformers/tokenization_utils_fast.py#L520) and [here](https://github.com/huggingface/transformers/blob/2e9af294940083915ccb2740a7c8d5b154194f15/src/transformers/tokenization_utils_fast.py#L472) respectively).<|||||>`prepare_for_model` is the only method that works like calling the tokenizer, but with input_ids as input (which is what several of my pre-processed datasets have). Is there another method call I could use that takes input_ids and includes the ability to add padding, truncation, etc...?<|||||>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.