[Model] Add support for Nanbeige4.2 (transformers backend)

[zqlcode]

Purpose

Add transformers backend support for Nanbeige 4.2 (NanbeigeForCausalLM):

Test Plan

vllm serve Nanbeige/Nanbeige4.2-3B \
  --trust-remote-code \
  --model-impl transformers \
  --host 0.0.0.0 \
  --port 8001 \
  --served-model-name nanbeige4.2-3b \
  --reasoning-parser qwen3 \
  --enable-auto-tool-choice \
  --tool-call-parser qwen3_coder \
  --tensor-parallel-size 2

Test Result

---

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• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

[claude]

Claude Code Review

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[github-actions]

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[hmellor]

Nice!

All that's missing is an entry in the test registry (maps the architecture to a checkpoint that we can use in CI) and a docs entry (tells users that your model is supported)

[hmellor]

Having this entry actually makes --model-impl transformers unnecessary, since vLLM is explicitly mapping your architecture to the Transformers impl.

Nothing to do here, I just wanted to explain.

[zqlcode]

Having this entry actually makes --model-impl transformers unnecessary, since vLLM is explicitly mapping your architecture to the Transformers impl.

Nothing to do here, I just wanted to explain.

Thanks for the review, @hmellor.

[mergify]

Documentation preview: https://vllm--56071.org.readthedocs.build/en/56071/

[hmellor]

I ran your model locally. The model loaded with:

(Worker pid=17861) INFO 09-10 16:12:56 [base.py:117] Using Transformers modeling backend.
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Found: 0 (NanbeigeLoopAttention) -> attention interface
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Found: 1 (NanbeigeLoopAttention) -> attention interface
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Fused: input_layernorm (NanbeigeRMSNorm) -> RMSNorm (CustomOp)
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Fused: post_attention_layernorm (NanbeigeRMSNorm) -> RMSNorm (CustomOp)
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Fused: norm (NanbeigeRMSNorm) -> RMSNorm (CustomOp)

And when queried it produced:

$ vllm complete -q 'Paris is'
 not the same as the Eiffel Tower. The Eiffel Tower is a structure, but

Which is coherent.

---

Note that the log doesn't include logs for QKVParallelLinear or the MergedColumnParallelLinear for the MLP. This is because of the pretraining_tp branches that are violating the Transformers backend's fusers.

This style of TP was removed a very long time ago (almost 2 years) in Transformers v4.54.1 (huggingface/transformers#34184) and I would recommend removing them from your custom code too.

[zqlcode]

I ran your model locally. The model loaded with:

(Worker pid=17861) INFO 09-10 16:12:56 [base.py:117] Using Transformers modeling backend.
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Found: 0 (NanbeigeLoopAttention) -> attention interface
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Found: 1 (NanbeigeLoopAttention) -> attention interface
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Fused: input_layernorm (NanbeigeRMSNorm) -> RMSNorm (CustomOp)
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Fused: post_attention_layernorm (NanbeigeRMSNorm) -> RMSNorm (CustomOp)
(Worker pid=17861) INFO 09-10 16:12:57 [base.py:560] Fused: norm (NanbeigeRMSNorm) -> RMSNorm (CustomOp)

And when queried it produced:

$ vllm complete -q 'Paris is'
 not the same as the Eiffel Tower. The Eiffel Tower is a structure, but

Which is coherent.

Note that the log doesn't include logs for QKVParallelLinear or the MergedColumnParallelLinear for the MLP. This is because of the pretraining_tp branches that are violating the Transformers backend's fusers.

This style of TP was removed a very long time ago (almost 2 years) in Transformers v4.54.1 (huggingface/transformers#34184) and I would recommend removing them from your custom code too.

Thanks @hmellor — fixed on the HF side by removing the legacy pretraining_tp branches.

[hmellor]

/ci run

[github-actions]

✅ Triggered Buildkite CI #88309 for commit 0e55036b51eb.

[hmellor]

/ci cancel

[hmellor]

Cancelled CI so you can fix DCO and update the docs with my suggestion

[zqlcode]

Cancelled CI so you can fix DCO and update the docs with my suggestion

Thanks! @hmellor Fixed DCO on all commits and updated the docs. Could you please /ci run again?

[zqlcode]

@hmellor updated the docs. Could you please /ci run again?

[hmellor]

/ci run

[github-actions]

✅ Triggered Buildkite CI #88822 for commit aea77d372949.