EfficientLLMInferenceCompetition/efficiency_samples_10pct

Muslim-language LLM efficiency-eval samples (public 10%)

Public 10% stratified sample of the private dataset EfficientLLMInferenceCompetition/efficiency_samples.

Workload for the NeurIPS 2026 competition proposal Efficient LLM Inference for Diverse Muslim Languages and Cultures.

This repo holds constructed GuideLLM Poisson traffic (not model weights). Lengths are measured with the official google/gemma-4-31B-it tokenizer including the chat template.

Sampling: seed 42, 200 conversations (40 per language), preserving the official mix (20/25/15/15/10/15). Some mixed conversations reuse a unique cell, so processed/ has 184 cells.

Files

Path	Description
mixed/conversations.jsonl	Primary set: 200 conversations (GuideLLM conversation_turns)
mixed/sidecar.jsonl	example_id → language / workload join keys
mixed/manifest.json	Mix counts, sample seed, and notes
mixed/single_turn.jsonl	170-row convenience split
mixed/multi_turn.jsonl	30-row convenience split
processed/{ar,fa,ur,bn,id}/*.jsonl	Unique cells used by this sample (184)
configs/benchmark.yaml	Frozen protocol (240 s windows, SLOs, λ fractions)
NOTICE	Third-party attribution (Aya Apache-2.0, Wikipedia CC BY-SA 4.0)

Languages (equal 20%)

Code	Language	Register	n
ar	Arabic	MSA only (dialects out of scope)	40
fa	Persian	Formal; preserve ZWNJ	40
ur	Urdu	Native script only (Roman Urdu out of scope)	40
bn	Bengali	Standard Bengali	40
id	Indonesian	Bahasa Indonesia only	40

Workload mix (experimental, not production traffic)

Workload	Input tokens	Output budget	Mix	n
short_interaction	64–512	16–128	20%	40
ordinary_single_turn	256–2048	128–512	25%	50
long_generation	256–2048	1024–4096	15%	30
long_context_short	8192–32768	64–512	15%	30
long_prompt_long_generation	8192–32768	1024–4096	10%	20
multi_turn_replay	3–8 turns; 512–16384 accumulated	64–512 / turn	15%	30

output_tokens_count is a credit cap (max_tokens), not a forced length.

Sources

Source	URL	License	Role
Aya (train)	https://huggingface.co/datasets/CohereForAI/aya_dataset	Apache-2.0	Short / ordinary seeds
Wikipedia (ar, fa, ur, bn, id)	MediaWiki API	CC BY-SA 4.0	Long documents and long-context bundles

Redistribute Wikipedia-derived text under CC BY-SA 4.0 with attribution. See NOTICE. Each mixed row has a license field (Apache-2.0 or CC BY-SA 4.0).

Protocol (summary)

• Measurement window: 240 s (plus 15 s warmup / 15 s cooldown)
• SLOs: TTFT < 10 s, decode ≥ 20 tok/s
• SUT = successful-user output tokens / window seconds (failed UX → 0)
• Score = mean(SUT_L, SUT_M, SUT_H) at 0.3 / 0.6 / 0.9 × λ_ref
• Arrivals: Poisson via GuideLLM

Load

from datasets import load_dataset

ds = load_dataset(
    "EfficientLLMInferenceCompetition/efficiency_samples_10pct",
    data_files="mixed/conversations.jsonl",
    split="train",
)