vllm-input-modalities

# vLLM — embeddings, reranking, speech-to-text, OCR Target audience: operators who need vLLM's non-chat-completion surfaces. Four capabilities bundled here because they share operator-facing concepts (`--runner` flag, pooling configuration, scoring API, multimodal preprocessing) even though two run on the pooling runner (embedding, reranking) and two run on the generate runner (STT, OCR). ## The mental model — one flag rules the surface vLLM decides what a model *does* from the combination of three flags: ``` --runner {auto|generate|pooling|draft} # what kind of workload --convert {auto|none|embed|classify} # adapt a generative LM to a pooler --pooler-config '{...}' # override pool type, dimensions, etc. ``` The pair `(runner, convert)` has replaced the old `--task {generate|embed| score|classify|reward|...}` flag. The old `--task` is **deprecated** and still works in current releases, but emits a deprecation warning and is scheduled for full removal. Canonical today: | Workload | Command | Runner | Notes | |---|---|---|---| | Chat / completion | `vllm serve <model>` | `generate` (auto) | default | | Embedding | `vllm serve <model> --runner pooling` | `pooling` | auto-detects CLS/LAST/MEAN from config | | Embedding from a causal LM | `vllm serve <model> --runner pooling --convert embed` | `pooling` | adapts `*ForCausalLM` checkpoints | | Classification | `vllm serve <model> --runner pooling --convert classify` | `pooling` | also how `scor...