A high-throughput and memory-efficient inference and serving engine for LLMs
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Synced Nov 8, 21:30 UTC
[docs] fix unintentional misspellings (#33863)
Signed-off-by: rinbaro <ilgomishra@gmail.com>
rinbaro committed
Feb 4, 2026 at 20:50 UTC
007b183d745f5b37aeb6cdf936c3b590b0c29fde
3 files changed
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docs/contributing/model/basic.md
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@@ -138,7 +138,7 @@ These models should follow the same instructions as case (1), but they should in
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For case (3), we recommend looking at the implementation of [`MiniMaxText01ForCausalLM`](../../../vllm/model_executor/models/minimax_text_01.py) or [`Lfm2ForCausalLM`](../../../vllm/model_executor/models/lfm2.py) as a reference, which use custom "mamba-like" layers `MiniMaxText01LinearAttention` and `ShortConv` respectively.
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Please follow the same guidelines as case (2) for implementing these models.
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-We use "mamba-like" to refer to layers that posses a state that is updated in-place, rather than being appended-to (like KV cache for attention).
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+We use "mamba-like" to refer to layers that possess a state that is updated in-place, rather than being appended-to (like KV cache for attention).
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For implementing new custom mamba-like layers, one should inherit from `MambaBase` and implement the methods `get_state_dtype`, `get_state_shape` to calculate the data types and state shapes at runtime, as well as `mamba_type` and `get_attn_backend`.
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It is also necessary to implement the "attention meta-data" class which handles the meta-data that is common across all layers.
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Please see [`LinearAttentionMetadata`](../../../vllm/v1/attention/backends/linear_attn.py) or [`ShortConvAttentionMetadata`](../../../vllm/v1/attention/backends/short_conv_attn.py) for examples of this.
docs/contributing/model/multimodal.md
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@@ -739,7 +739,7 @@ Each [PromptUpdate][vllm.multimodal.processing.PromptUpdate] instance specifies
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```
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However, this is not entirely correct. After `FuyuImageProcessor.preprocess_with_tokenizer_info` is called,
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- a BOS token (`<s>`) is also added to the promopt:
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+ a BOS token (`<s>`) is also added to the prompt:
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??? code
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docs/getting_started/quickstart.md
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@@ -57,7 +57,7 @@ This guide will help you quickly get started with vLLM to perform:
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It currently supports Python 3.12, ROCm 7.0 and `glibc >= 2.35`.
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!!! note
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- Note that, previously, docker images were published using AMD's docker release pipeline and were located `rocm/vlm-dev`. This is being deprecated by using vLLM's docker release pipeline.
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+ Note that, previously, docker images were published using AMD's docker release pipeline and were located `rocm/vllm-dev`. This is being deprecated by using vLLM's docker release pipeline.
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=== "Google TPU"
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