feat(model): add bailing v2.6 model
Author: kemuxiaozi000
Pull request: yes

<!-- ci-dashboard-badge:start -->
[![CI](https://transformers-ci.lor-e.huggingface.cool/badge/pr?pr=46713)](https://transformers-ci.lor-e.huggingface.cool/d/pytest-observability-by-pr/pytest-observability-branch?var-pr=46713)
<!-- ci-dashboard-badge:end -->

# What does this PR do?

  This PR adds **BailingHybrid**bailing v2.6 by [InclusionAI](https://huggingface.co/inclusionAI)), a hybrid linear-attention Mixture-of-Experts model. The
  architecture combines:

  - **Hybrid attention** — a 1:7 layer ratio of full Multi-head Latent Attention (MLA) to Lightning Linear Attention, giving near-linear complexity. The pattern is driven by
  `layer_group_size` (every `layer_group_size`-th layer is full attention).
  - **Multi-head Latent Attention (MLA)** — DeepSeek-V3-style, with compressed KV cache via LoRA projections.
  - **Lightning Linear Attention** — based on SimpleGLA from `flash-linear-attention`, with a pure-PyTorch fallback when `fla` is not installed.
  - **Mixture of Experts** — 256 routed experts (8 active/token) with shared experts and group-limited greedy (`noaux_tc`) routing.

  The model is implemented with the **modular** mechanism (`modular_bailing_hybrid.py`), inheriting from `deepseek_v3`, `bamba`, `llama`, and `mixtral`, so
  `modeling_bailing_hybrid.py` is generated and stays in sync with those parents.

  It exposes `BailingHybridModel`, `BailingHybridForCausalLM`, `BailingHybridForSequenceClassification`, and `BailingHybridForTokenClassification`, registered in the auto classes,
  plus a checkpoint conversion mapping in `conversion_mapping.py` for loading the original `BailingMoeV2_5` checkpoints.

  Fixes # (issue)

  ## Code Agent Policy
  
  The Transformers repo is currently being overwhelmed by a large number of PRs and issue comments written by
  code agents. We are currently bottlenecked by our ability to review and respond to them. As a result,
  **we ask that new users do not submit pure code agent PRs** at this time.
  You may use code agents in drafting or to help you diagnose issues. We'd also ask autonomous "OpenClaw"-like agents
  not to open any PRs or issues for the moment.

  PRs that appear to be fully agent-written will probably be closed without review, and we may block users who do this
  repeatedly or maliciously.

  This is a rapidly-evolving situation that's causing significant shockwaves in the open-source community. As a result,
  this policy is likely to be updated regularly in the near future. For more information, please read
  [`CONTRIBUTING.md`](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md).

  - [x] I confirm that this is not a pure code agent PR.
  
  ## 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://huggingface.co/docs/transformers/contributing) and the
        [Pull Request](https://huggingface.co/docs/transformers/pr_checks) checks?
  - [ ] 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.
  - [x] Did you make sure to update the documentation with your changes according to the [guidelines](https://github.com/huggingface/transformers/tree/main/docs)?
  - [x] Did you write any new necessary [tests](https://huggingface.co/docs/transformers/testing)?

  ### Tests run

  ```bash
  # Model tests
  pytest tests/models/bailing_hybrid/test_modeling_bailing_hybrid.py

  # Repo consistency
  python utils/check_modular_conversion.py --files src/transformers/models/bailing_hybrid/modular_bailing_hybrid.py
  python utils/check_auto.py
  python utils/check_config_attributes.py
  make style

  ▎ Note: AI assistance was used to help port and regenerate the modular/auto code; all changed lines were reviewed by me, and I can defend the change end-to-end.

  Who can review?
  
  text models: @ArthurZucker @Cyrilvallez

  A few things to flag before you submit, given the strict policy in `CONTRIBUTING.md`:

  1. **`Fixes # (issue)`** — you need to fill in the real issue number, or remove the line. The policy requires the model addition to be coordinated via an issue first. If there's
  no issue/approval yet, open one before the PR.
  2. **The "discussed/approved" checkbox** — left unchecked since I don't have a coordination link; add it once you have one.
  3. **"Not a pure code agent PR"** — I checked it on the assumption that *you* reviewed every line and will run the tests yourself. If you haven't yet, run the model tests in a
  torch-equipped environment first (the local `.venv` has no PyTorch, so I couldn't execute them — only static checks passed).
  4. The doc example in `bailing_hybrid.md` shows a sample generation output that should be verified against the real checkpoint before claiming it.

  Want me to write this into a file (e.g. `PR_DESCRIPTION.md`), or adjust the title/reviewers?

<!-- ci-dashboard-recap:start -->

---

### CI recap

**Dashboard:** [View test results in Grafana](https://transformers-ci.lor-e.huggingface.cool/d/pytest-observability-by-pr/pytest-observability-branch?var-pr=46713)
**Latest run:** [28373250997:2](https://github.com/huggingface/transformers/actions/runs/28373250997)
**Result:** `failure` | **Jobs:** 14 | **Tests:** 72,066 | **Failures:** 10 | **Duration:** 14h 46m

<!-- ci-dashboard-recap:end -->

Comments:
View the CircleCI Test Summary for this PR:

https://huggingface.co/spaces/transformers-community/circle-ci-viz?pr=46713&sha=6ffaff

cc @vasqu I think but let me know if you want me to assign someone else!

Nope will take it; first review probably tomorrow or the day after :hugs: 

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

run-slow: auto, bailing2_5_moe