tools : enable kvu in perplexity for hellaswag, winogrande, multiple-choice#19954
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angt merged 1 commit intoggml-org:masterfrom Mar 13, 2026
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…choice
llama-perplexity -hf unsloth/Qwen3-0.6B-GGUF:Q4_K_M -f winogrande-debiased-eval.csv --winogrande
winogrande_score : tokenizing selected tasks
winogrande_score : calculating winogrande score over selected tasks.
split_equal: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag)
decode: failed to find a memory slot for batch of size 46
failed to decode the batch, n_batch = 2048, ret = 1
winogrande_score: llama_decode() failed
same for hellaswag:
split_equal: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag)
decode: failed to find a memory slot for batch of size 99
failed to decode the batch, n_batch = 2048, ret = 1
hellaswag_score: llama_decode() failed
Signed-off-by: Adrien Gallouët <[email protected]>
angt
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cc @ggerganov |
ggerganov
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Mar 13, 2026
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Think it is OK as proposed. |
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Mar 20, 2026
…choice (ggml-org#19954) llama-perplexity -hf unsloth/Qwen3-0.6B-GGUF:Q4_K_M -f winogrande-debiased-eval.csv --winogrande winogrande_score : tokenizing selected tasks winogrande_score : calculating winogrande score over selected tasks. split_equal: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag) decode: failed to find a memory slot for batch of size 46 failed to decode the batch, n_batch = 2048, ret = 1 winogrande_score: llama_decode() failed same for hellaswag: split_equal: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag) decode: failed to find a memory slot for batch of size 99 failed to decode the batch, n_batch = 2048, ret = 1 hellaswag_score: llama_decode() failed Signed-off-by: Adrien Gallouët <[email protected]>
mudler
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Mar 31, 2026
The hybrid memory paths (`llama-memory-hybrid.cpp` and `llama-memory-hybrid-iswa.cpp`) always used sequential equal split, ignoring the unified KV cache flag. This caused hellaswag, winogrande, and multiple-choice evaluations to fail on hybrid models (models with both attention and recurrent/SSM layers, such as Qwen3.5-35B-A3B) with: split_equal: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag) PR ggml-org#19954 fixed this for `llama-kv-cache-iswa.cpp` by automatically enabling unified KV mode and setting n_parallel >= 4 for multi-choice eval tasks. However, the hybrid memory paths were not updated. This commit mirrors the iswa fix: use non-sequential split when KV cache is unified (n_stream == 1), which is automatically set by llama-perplexity for hellaswag/winogrande/multiple-choice since ggml-org#19954. Tested on Qwen3.5-35B-A3B (hybrid attention+SSM MoE model): - HellaSwag: 83.0% (400 tasks) - Winogrande: 74.5% (400 tasks) - MMLU: 41.2% - ARC-Challenge: 56.2% - TruthfulQA: 37.7% All previously failed with llama_decode() error.
ggerganov
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Apr 1, 2026
) The hybrid memory paths (`llama-memory-hybrid.cpp` and `llama-memory-hybrid-iswa.cpp`) always used sequential equal split, ignoring the unified KV cache flag. This caused hellaswag, winogrande, and multiple-choice evaluations to fail on hybrid models (models with both attention and recurrent/SSM layers, such as Qwen3.5-35B-A3B) with: split_equal: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag) PR #19954 fixed this for `llama-kv-cache-iswa.cpp` by automatically enabling unified KV mode and setting n_parallel >= 4 for multi-choice eval tasks. However, the hybrid memory paths were not updated. This commit mirrors the iswa fix: use non-sequential split when KV cache is unified (n_stream == 1), which is automatically set by llama-perplexity for hellaswag/winogrande/multiple-choice since #19954. Tested on Qwen3.5-35B-A3B (hybrid attention+SSM MoE model): - HellaSwag: 83.0% (400 tasks) - Winogrande: 74.5% (400 tasks) - MMLU: 41.2% - ARC-Challenge: 56.2% - TruthfulQA: 37.7% All previously failed with llama_decode() error.
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llama-perplexity -hf unsloth/Qwen3-0.6B-GGUF:Q4_K_M -f winogrande-debiased-eval.csv --winogrande
same for hellaswag: