Add Qwen2Moe GGUF loading support 
Author: VladOS95-cyber
Pull request: yes

# What does this PR do?

<!--
Congratulations! You've made it this far! You're not quite done yet though.

Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.

Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.

Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
-->

<!-- Remove if not applicable -->

Add Qwen2Moe GGUF loading support


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [x] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case. Link: https://github.com/huggingface/transformers/issues/33260
- [x] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [x] Did you write any new necessary tests?


## Who can review?
Regarding the task @SunMarc @LysandreJik @ArthurZucker .

<!-- Your PR 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:

- text models: @ArthurZucker
- vision models: @amyeroberts
- speech models: @sanchit-gandhi
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Narsil
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @sanchit-gandhi
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->


Comments:
Hello @SunMarc @LysandreJik @ArthurZucker! I would like to ask for a code review 

> Thanks for this clean PR @vanpelt ! LGTM !

Thank you for review! Why @vanpelt? =))

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_33264). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

> Thank you for review! Why @vanpelt? =))

My bad, editted ;) usually the first name github suggests me is the author of the PR 

> > Thank you for review! Why @vanpelt? =))
> 
> My bad, editted ;) usually the first name github suggests me is the author of the PR

No worries at all :)

Anytime guy's 🤪.  Nice work @VladOS95-cyber!

I'm hitting an error on our CI and locally for this test `test_qwen2_moe_q4_0` @VladOS95-cyber . Can you have a look? 
Here's the traceback: 

```python
self = <ggml.test_ggml.GgufIntegrationTests testMethod=test_qwen2_moe_q4_0>

    def test_qwen2_moe_q4_0(self):
        tokenizer = AutoTokenizer.from_pretrained(self.qwen2_moe_model_id, gguf_file=self.q4_0_qwen2_moe_model_id)
        model = AutoModelForCausalLM.from_pretrained(
            self.qwen2_moe_model_id,
            gguf_file=self.q4_0_qwen2_moe_model_id,
            device_map="auto",
            torch_dtype=torch.float16,
        )

        text = tokenizer(self.example_text, return_tensors="pt").to(torch_device)
        out = model.generate(**text, max_new_tokens=10)

        EXPECTED_TEXT = "Hello everyone, I'm a newbie here and would like"
>       self.assertEqual(tokenizer.decode(out[0], skip_special_tokens=True), EXPECTED_TEXT)
E       AssertionError: 'Hello部分齐值得关注erc区域堪称 btnCancel跳舞�ASC' != "Hello everyone, I'm a newbie here and would like"
E       - Hello部分齐值得关注erc区域堪称 btnCancel跳舞�ASC
E       + Hello everyone, I'm a newbie here and would like

tests/quantization/ggml/test_ggml.py:359: AssertionError
```

Also here's some interesting logs: 

```
Some weights of Qwen2MoeForCausalLM were not initialized from the model checkpoint at RichardErkhov/Qwen_-_Qwen1.5-MoE-A2.7B-Chat-gguf and are newly initialized: ['model.layers.0.mlp.experts.0.down_proj.weight', 'model.layers.0.mlp.experts.0.gate_proj.weight', 'model.layers.0.mlp.experts.0.up_proj.weight', 'model.layers.0.mlp.experts.1.down_proj.weight', 'model.layers.0.mlp.experts.1.gate_proj.weight', 'model.layers.0.mlp.experts.1.up_proj.weight', 'model.layers.0.mlp.experts.10.down_proj.weight', 'model.layers.0.mlp.experts.10.gate_proj.weight', 'model.layers.0.mlp.experts.10.up_proj.weight', 'model.layers.0.mlp.experts.11.down_proj.weight', 'model.layers.0.mlp.experts.11.gate_proj.weight', 'model.layers.0.mlp.experts.11.up_proj.weight', 'model.layers.0.mlp.experts.12.down_proj.weight', 'model.layers.0.mlp.experts.12.gate_proj.weight', 'model.layers.0.mlp.experts.12.up_proj.weight', 
.....
```

Looks like we didn't manage to load the weights correctly. Also the GgufIntegrationTests.test_bloom_q8_0 test is also failing but it is easier to fix: 

```
>       self.assertEqual(tokenizer.decode(out[0], skip_special_tokens=True), EXPECTED_TEXT)
E       AssertionError: 'Hello, I just want to say that I am just' != 'Hello, I just want to say that I am very'
E       - Hello, I just want to say that I am just
E       ?                                     ^^^^
E       + Hello, I just want to say that I am very
E       ?                                     ^^^^

tests/quantization/ggml/test_ggml.py:422: AssertionError
```

@SunMarc sure, I'll take a look