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…SparkModel Signed-off-by: Andrii Skliar <askliar@nvidia.com>
Signed-off-by: Andrii Skliar <askliar@nvidia.com>
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Signed-off-by: Andrii Skliar <askliar@nvidia.com> Co-authored-by: Andrii Skliar <askliar@nvidia.com> Co-authored-by: Benjamin Chislett <bchislett@nvidia.com> (cherry picked from commit b977407)
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…alError) The rebase onto v0.27.1 merged upstream vllm-project#50424's quant_config into DSparkMarkovHead.__init__ but dropped the fork's keyword-only shard_vocab: bool | None = None parameter during conflict resolution, while keeping the body hunk that reads it. At model load every DSpark draft model (DSv4-NVIDIA/Qwen3) hits 'if shard_vocab is None:' with shard_vocab never bound -> UnboundLocalError at qwen3_dspark.py:89. Restore the keyword-only shard_vocab parameter after quant_config; all callers pass their args by keyword (prod and tests), so the signature stays backward compatible.
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Summary
Add quantization configuration support to the DSpark Markov head.
DSparkMarkovHeadnow accepts and forwardsquant_configto itsParallelLMHead-basedmarkov_w2projection.Qwen3DSparkModelpasses its model quantization configuration when constructing the Markov head.This allows quantized
markov_w2weights, including W4A16 configurations withweight_scale_2, to load through the normal quantization dispatch path while preserving unquantized behavior.Testing
Attempted DSpark quantization and loading with this branch.