Add DINOv3Backbone for ConvNext variant
Author: merveenoyan
Pull request: yes

I've taken a stab as it was a convolutional model it's very straightforward. The tests I borrowed from Dinov2, I hope it's ok @qubvel can you review if you have bandwidth? 

If it's good I will try with AIMv2, PE and some other image backbones as well! 

Comments:
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checking the issue with consistency

tests were passing locally, checking

the model downsamples with stride=4 in stem and then stride=2, which is different from convnext (which I borrowed tests from) so I fixed expected shape 

Hey @merveenoyan! Sorry I think I'm missing some context here, why do we need to add this? 🤗 I don't see it used anywhere else 

@Cyrilvallez this API wasn't used a lot, it allows us to use `image-feature-extraction` or `image-classification` models to have a custom heads like DETR like lego blocks, this is an attempt to revive the API and later we'll demonstrate how it's used to get it adopted
the backbones we have are very old as we didn't add a lot of backbones after the launch of the API

cc @yonigozlan as well

@ArthurZucker @yonigozlan @qubvel 
I have trained a model for four epochs just to test if it converges, here's results and the model: https://huggingface.co/merve/license-plate-detr-dinov3 is it ok? 👀

<img width="1131" height="520" alt="Screenshot 2025-09-26 at 17 36 22" src="https://github.com/user-attachments/assets/727daba2-7749-4086-b155-2cd07f6d006c" />
<img width="686" height="361" alt="Screenshot 2025-09-26 at 17 35 01" src="https://github.com/user-attachments/assets/91e57251-e4f9-40bf-ace1-ed11c80c3082" />
<img width="614" height="354" alt="Screenshot 2025-09-26 at 17 35 23" src="https://github.com/user-attachments/assets/6552ffea-4b1a-49b8-9014-3e0cdb794a49" />


Hey @merveenoyan I'm not very familiar with BackboneMixin and its usage, but trusting you if you think this could be useful for users! Also agreed with @ArthurZucker, it looks like this could be automated? The only difference with DINOv3ConvNextModel is that we don't apply pooling + layernorm, and I'm guessing there is a similar pattern for other Backbone models?
It seems a bit redundant to me to have both DINOv3ConvNextModel and DINOv3ConvNextBackbone (can Dinov3 be used as something other than a backbone?), but I might be missing something

Just to keep in mind and connect the PRs https://github.com/huggingface/transformers/pull/41276 

@yonigozlan I think the point of the API was that you can extract different features in different stages and pass it to any head. I would like to merge this, see if the community likes it and then come up with a way that we don't need to add backbones because I also don't find it scalable and it seems redundant. Thank you!

I see! That makes sense, indeed would be great to give more exposure to this, I see there's already some doc. Maybe to avoid redundancy, we could remove/deprecate basic Model if there also exists a backbone for it? Unless you think it makes sense to have both?
Wdyt @merveenoyan @molbap ?

fyi @yonigozlan I have also [made this documentation](https://colab.research.google.com/drive/1qfBOIIdb5ytKKGlfoCqZtmeDvt5aVDAa?usp=sharing) I will open a follow-up PR 🙌🏻

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: auto, dinov3_convnext

I got the pass from Yoni in-person 😄