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[Doc] Update V1 Guide for embedding models (#19141)
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
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@ -55,7 +55,7 @@ This living user guide outlines a few known **important changes and limitations*
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| **Spec Decode** | <nobr>🚧 WIP ([PR #13933](https://github.com/vllm-project/vllm/pull/13933))</nobr>|
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| **Prompt Logprobs with Prefix Caching** | <nobr>🟡 Planned ([RFC #13414](https://github.com/vllm-project/vllm/issues/13414))</nobr>|
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| **Structured Output Alternative Backends** | <nobr>🟡 Planned</nobr> |
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| **Embedding Models** | <nobr>🚧 WIP ([PR #18015](https://github.com/vllm-project/vllm/pull/18015))</nobr> |
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| **Embedding Models** | <nobr>🚧 WIP ([PR #16188](https://github.com/vllm-project/vllm/pull/16188))</nobr> |
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| **Mamba Models** | <nobr>🟡 Planned</nobr> |
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| **Encoder-Decoder Models** | <nobr>🟠 Delayed</nobr> |
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| **Request-level Structured Output Backend** | <nobr>🔴 Deprecated</nobr> |
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@ -145,9 +145,9 @@ vLLM V1 currently excludes model architectures with the `SupportsV0Only` protoco
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and the majority fall into the following categories. V1 support for these models will be added eventually.
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**Embedding Models**
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Initially, we will create a [separate model runner](https://github.com/vllm-project/vllm/pull/18015) to provide V1 support without conflicting with other ongoing work.
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The initial support will be provided by [PR #16188](https://github.com/vllm-project/vllm/pull/16188).
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Later, we will consider using [hidden states processor](https://github.com/vllm-project/vllm/issues/12249), which is based on [global logits processor](https://github.com/vllm-project/vllm/pull/13360) to enable simultaneous generation and embedding using the same engine instance in V1. [PR #16188](https://github.com/vllm-project/vllm/pull/16188) is the first step towards enabling this.
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Later, we will consider using [hidden states processor](https://github.com/vllm-project/vllm/issues/12249), which is based on [global logits processor](https://github.com/vllm-project/vllm/pull/13360) to enable simultaneous generation and embedding using the same engine instance in V1.
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**Mamba Models**
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Models using selective state-space mechanisms (instead of standard transformer attention)
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