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token_embed & token_classify
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docs/models/pooling_models.md

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@@ -30,11 +30,11 @@ If `--runner pooling` has been set (manually or automatically) but the model doe
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vLLM will attempt to automatically convert the model according to the architecture names
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shown in the table below.
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| Architecture | `--convert` | Supported pooling tasks |
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|-------------------------------------------------|-------------|-------------------------------|
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| `*ForTextEncoding`, `*EmbeddingModel`, `*Model` | `embed` | `encode`, `embed` |
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| `*For*Classification`, `*ClassificationModel` | `classify` | `encode`, `classify`, `score` |
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| `*ForRewardModeling`, `*RewardModel` | `reward` | `encode` |
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| Architecture | `--convert` | Supported pooling tasks |
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|-------------------------------------------------|-------------|---------------------------------------|
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| `*ForTextEncoding`, `*EmbeddingModel`, `*Model` | `embed` | `token_embed`, `embed` |
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| `*For*Classification`, `*ClassificationModel` | `classify` | `token_classify`, `classify`, `score` |
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| `*ForRewardModeling`, `*RewardModel` | `reward` | `token_classify` |
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!!! tip
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You can explicitly set `--convert <type>` to specify how to convert the model.

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