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.Nemotron-SFT-CUDA-v1
Dataset Description:
Nemotron-SFT-CUDA-v1 is a training dataset for CUDA code. It helps language models write CUDA kernels and solve CUDA programming problems.
We start from CUDA code in Nemotron Pretraining Code v2, which has a permissive license. An OpenCode agent powered by GLM-4.7 reads that code and writes new CUDA programming problems. Each problem comes with a hidden answer and tests. A second OpenCode + GLM-4.7 agent then tries to solve the problems using only the prompt… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-CUDA-v1.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.r8-thinking-fix-sft
⚠️ 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 Thinking-Fix SFT… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r8-thinking-fix-sft.r7-additive-sft
⚠️ 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.
R7 Additive SFT… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r7-additive-sft.Astra-COT-40K
High Quality Reasoning Chat Dataset
A curated conversational dataset designed for instruction tuning and reasoning-focused language model training.
The corpus contains high-quality multi-turn conversations, detailed explanations, coding examples, analytical tasks, and explicit reasoning traces (<think>...</think>). The dataset was normalized into a standard chat format and filtered to remove duplicate conversations while preserving the original responses and reasoning behavior.… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/Astra-COT-40K.r8b-tool-sft
⚠️ 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.
R8b Tool-Deferral +… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r8b-tool-sft.CUDABench-Setr8-calibration-sft
⚠️ 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 Calibration SFT… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r8-calibration-sft.sn96g-nvidia-cuda-2chunk1-20250919_193141
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 2
Avg answer length (tokens): 24.5 (median 24.5, min 23, max 26)
Schema errors: 0 (should be 0)
File size: 0.00 MB
SHA256 (data.jsonl): 0ecd861d6eb5db044497d6cee50581bc262d81c9bde97b250d71492d5ded1cd9
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-nvidia-cuda-2chunk1-20250919_193141.CUDA-INSTRUCTsn96g-nvidia-cuda-2chunk1-20250919_184205
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 2
Avg answer length (tokens): 13 (median 13.0, min 10, max 16)
Schema errors: 0 (should be 0)
File size: 0.00 MB
SHA256 (data.jsonl): 2634de9ae8dac993c2c012306caa23818f74ef3ab3dc44d2f2359b48ae261aa1
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-nvidia-cuda-2chunk1-20250919_184205.sn96g-nvidia-cuda-10chunk1-20250919_132945
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 33
Avg answer length (tokens): 121.7 (median 124, min 85, max 177)
Schema errors: 0 (should be 0)
File size: 0.03 MB
SHA256 (data.jsonl): be526551fda405d26500c0f33266fe7e664685ee055d8aa687c9a37fa13e032f
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-nvidia-cuda-10chunk1-20250919_132945.sn96g-nvidia-cuda-2chunk1-20250919_175127
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 2
Avg answer length (tokens): 34.5 (median 34.5, min 31, max 38)
Schema errors: 0 (should be 0)
File size: 0.00 MB
SHA256 (data.jsonl): 48e31897063eaaed8a28718772e0708ffd9900e30a85d129cf3745fe57fa6d59
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-nvidia-cuda-2chunk1-20250919_175127.