Add full GGUF loading support for GPT‑OSS (fixes #43366, supersedes #43757) latest

[sirzechs66]

What does this PR do?

This PR adds full GGUF loading support for GPT‑OSS models (20B/120B). It allows Transformers (and consequently vLLM) to directly load GPT‑OSS GGUF files without falling back to a wrong architecture. The changes include:

• Architecture registration in GGUF mappings.
• A custom GptOssTensorProcessor to handle MoE expert splitting and gate/up interleaving.
• Reconstruction of nested rope_scaling (YaRN) from flat GGUF metadata.
• Tests: fast registration test + slow integration test using a real 20B GGUF file.

Fixes #43366, supersedes #43757.
Related vLLM issue: vllm-project/vllm#22353

Code Agent Policy

• 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). – Not applicable, it adds a feature.
• Did you read the contributor guideline, Pull Request section? – Yes.
• Was this discussed/approved via a Github issue or the forum? Please add a link to it if that's the case. – Issue GGUF model with architecture gpt-oss support #43366, discussion in comments.
• Did you make sure to update the documentation with your changes? – yes!
• Did you write any new necessary tests? – Yes, in test/quantization/test_ggml.py

Who can review?

Anyone in the community is free to review the PR once the tests have passed. Tagging:

• @SunMarc (original issue tagger, quantization)
• @Cyrilvallez (model loading)
• @ArthurZucker (tokenizers, model structure)

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

run-slow: ggml

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View the CircleCI Test Summary for this PR:

https://huggingface.co/spaces/transformers-community/circle-ci-viz?pr=45500&sha=483e8f