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[Model][2/N] Automatic conversion of CrossEncoding model (#19978)

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Signed-off-by: wang.yuqi <noooop@126.com>
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wang.yuqi
2025-07-03 21:59:23 +08:00
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parent 1819fbda63
commit 6f1229f91d
16 changed files with 199 additions and 92 deletions
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2
docs/models/supported_models.md
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@@ -471,7 +471,7 @@ Specified using `--task classify`.
| `JambaForSequenceClassification` | Jamba | `ai21labs/Jamba-tiny-reward-dev`, etc. | ✅︎ | ✅︎ | |
| `GPT2ForSequenceClassification` | GPT2 | `nie3e/sentiment-polish-gpt2-small` | | | ✅︎ |
If your model is not in the above list, we will try to automatically convert the model using
[as_classification_model][vllm.model_executor.models.adapters.as_classification_model]. By default, the class probabilities are extracted from the softmaxed hidden state corresponding to the last token.
[as_seq_cls_model][vllm.model_executor.models.adapters.as_seq_cls_model]. By default, the class probabilities are extracted from the softmaxed hidden state corresponding to the last token.
#### Sentence Pair Scoring

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docs/serving/openai_compatible_server.md
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@@ -426,7 +426,7 @@ Code example: <gh-file:examples/online_serving/openai_pooling_client.py>
Our Classification API directly supports Hugging Face sequence-classification models such as [ai21labs/Jamba-tiny-reward-dev](https://huggingface.co/ai21labs/Jamba-tiny-reward-dev) and [jason9693/Qwen2.5-1.5B-apeach](https://huggingface.co/jason9693/Qwen2.5-1.5B-apeach).
We automatically wrap any other transformer via `as_classification_model()`, which pools on the last token, attaches a `RowParallelLinear` head, and applies a softmax to produce per-class probabilities.
We automatically wrap any other transformer via `as_seq_cls_model()`, which pools on the last token, attaches a `RowParallelLinear` head, and applies a softmax to produce per-class probabilities.
Code example: <gh-file:examples/online_serving/openai_classification_client.py>