datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
p2026-002-quantization-context-compression-results
Deployed Quantization Tier and Lossy Context Compression in Extractive QA
This result dataset mirrors the version-1.0.0 reproducibility artifact:
10.5281/zenodo.22847291.
The versioned report and full replication sources
are maintained together in the research-artifacts repository. Cite the exact
Zenodo version for the frozen evidence; this Hugging Face copy is a discovery
mirror.
Matthew Schwartz — ORCID 0009-0009-4171-7247
This dataset is the aggregate-only evidence for "No… See the full description on the dataset page: https://huggingface.co/datasets/mv1137/p2026-002-quantization-context-compression-results.quantization-benchmarksdiffusers-quantization-benchmarksh200-quantization-benchmarks
H200 Quantization Benchmarks
Benchmark results for 40 quantized and non-quantized instruction-tuned LLMs evaluated on an NVIDIA H200 MIG (Multi-Instance GPU) setup. This dataset supports reproducible comparison of quantization methods (AWQ, GPTQ, fp8, bf16) across accuracy and throughput dimensions.
Dataset Configs
Config
Description
Rows
accuracy
Per-task accuracy results from lm-eval across all models
~240
accuracy_leaderboard
Aggregated accuracy… See the full description on the dataset page: https://huggingface.co/datasets/ssakethch/h200-quantization-benchmarks.EXAONE-4.0-1.2B-Quantization-MMLU