datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
kernelbench-cuda-tracesdim58-cudaData-31cases
Dim58 CPU Data — 31 Cases
Dataset uploaded from:
/mnt/data/ubuntu/research/outputs/data_cuda_geodesic58
Dataset summary
Property
Value
Repository
hosseinbv/dim58-cudaData-31cases
Number of files
64
Total size
17.99 GB
Source folder
data_cuda_geodesic58
File types
Extension
File count
.npz
62
.json
1
.csv
1
Top-level contents
0000_internal_case1_data.npz
0001_internal_B_10.npz… See the full description on the dataset page: https://huggingface.co/datasets/hosseinbv/dim58-cudaData-31cases.r8-eval-suite-5bucket
⚠️ CRITICAL: Ollama Inference Flag Required for derived models
If you train or serve any Qwen3.5-9B-derived model from this lineage via Ollama,
you MUST pass "think": false in /api/chat requests for chat / instruction following / tool use.
The qwen3.5 RENDERER auto-injects <think> tags causing 25-46% empty-answer rates without this flag.
See dataset cudabenchmarktest/r9-research-framework/_OLLAMA_INFERENCE_WARNING.md for the full lesson learned.
R8/R9 Five-Bucket… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r8-eval-suite-5bucket.maple-preview-cuda-benchmarks
Maple Preview TQ2_0 CUDA Benchmarks
Reproducibility data for the TQ2_0 CUDA patches in
PascalAI2024/maple-preview-windows-cuda.
This repository contains benchmark data, patch files, hashes, and raw validation
evidence. It does not duplicate the Maple model weights.
Result
The fresh local A/B/B/A validation on an RTX 4080 SUPER reproduced the fused-MMQ
prompt-processing gain:
Variant
pp512 mean
pp512 median
tg128 mean
tg128 median
Correctness
MMQ enabled… See the full description on the dataset page: https://huggingface.co/datasets/x0me/maple-preview-cuda-benchmarks.r9-research-framework
R9 Research Framework — Qwen3.5-9B Distillation
⚠️ CRITICAL: READ FIRST — Ollama Inference Flag Required
If you serve any Qwen3.5-derived model from this lineage via Ollama,
you MUST pass "think": false in the /api/chat request body.
curl -X POST http://localhost:11434/api/chat \
-d '{"model": "qwen3.5-9b-r10:q4km", "think": false, "messages": [...], "stream": false}'
Without this flag the model will appear to "loop" and produce empty answers
on 25-46% of requests.… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r9-research-framework.cuda-nsys-training
Qwythos Nsight Systems Profiling Agent Dataset
Multi-turn GPU profiling agent trajectories for fine-tuning Qwythos-9B (and similar tool-calling models) on NVIDIA Nsight Systems (nsys) + CUDA-L1 / KernelBench workloads.
Generated autonomously on an RTX 5090 by the model itself driving real profiling tools for ~33 hours.
Code: ai-hpc/prof-dataset-gen
Stats
Split
Rows
Notes
train
5,884
Accepted episodes (quality ≥ 0.55)
eval
309
5% holdout from accepted… See the full description on the dataset page: https://huggingface.co/datasets/gittensor-model-hub/cuda-nsys-training.