Provide more useful error message in Detr from_pretrained when timm not installed
Author: nateraw
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: master
- Platform: Google Colab
- Python version: 3.7
- PyTorch version (GPU?):1.8.1+cu101
- Tensorflow version (GPU?):N/A
- Using GPU in script?:N/A
- Using distributed or parallel set-up in script?:N/A

### Who can help
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @Rocketknight1

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

Model hub:

- for issues with a model report at https://discuss.huggingface.co/ and tag the model's creator.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->

## Information

Model I am using (Bert, XLNet ...):

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

[Here's a colab notebook.
](https://colab.research.google.com/drive/1b8RVCARcZU8kBFywRID8ZLPAYwhcd10p?usp=sharing)

1. install latest transformers from master w/o installing `timm`.
2. Try to init any `DetrModel` `from_pretrained`, and you'll see you get a misleading error
```python
from transformers import DetrForObjectDetection

model = DetrForObjectDetection.from_pretrained('facebook/detr-resnet-50')
```

Error thrown:

```bash
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-175d7bae5f8e> in <module>()
      1 from transformers import DetrForObjectDetection
      2 
----> 3 model = DetrForObjectDetection.from_pretrained('facebook/detr-resnet-50')

AttributeError: type object 'DetrForObjectDetection' has no attribute 'from_pretrained'
```

3. Try the same w/ timm installed, and see that it works.


<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

Have message informing user that they must have `timm` installed to use `from_pretrained` with `Detr` models instead of just telling them there is no attribute `from_pretrained`.

Comments:
Thanks for raising an issue! Fixing this in #12097 

Thanks for already testing out the model! Highly appreciate your feedback. If anything related to the model/docs can be improved, feel free to reach out.