datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
vllm-control-arena
vLLM Main Tasks Dataset
AI coding tasks generated from vLLM git commits
Dataset Description
This dataset contains 6801 coding tasks automatically generated from git commits in the vLLM repository. Each task represents a real-world coding challenge derived from actual development work.
Dataset Structure
The dataset contains the following columns:
commit_hash: The git commit hash
parent_hash: The parent commit hash
commit_title: The original commit… See the full description on the dataset page: https://huggingface.co/datasets/RoganInglis/vllm-control-arena.VLLM_ChartQAdetails_hosted_vllm____fsx__anton__deepseek-r1-checkpoint_private
Dataset Card for Evaluation run of hosted_vllm//fsx/anton/deepseek-r1-checkpoint
Dataset automatically created during the evaluation run of model hosted_vllm//fsx/anton/deepseek-r1-checkpoint.
The dataset is composed of 15 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 9 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/SaylorTwift/details_hosted_vllm____fsx__anton__deepseek-r1-checkpoint_private.MIRB-hfQwen2.5-7B-Instruct-vllm-20251128_042753grammar-accuracy-qwen3.5-4b-trl-grpo-vllm-colocate-completions
TRL Completion logs
This dataset contains the completions generated during training using trl.
Find the trained model at https://huggingface.co/bihungba1101/grammar-accuracy-qwen3.5-4b-trl-grpo-vllm-colocate.
The completions are stored in parquet files, and each file contains the completions for a single step of training (depending on the logging_steps argument).
Each file contains the following columns:
step: the step of training
prompt: the prompt used to generate the completion… See the full description on the dataset page: https://huggingface.co/datasets/bihungba1101/grammar-accuracy-qwen3.5-4b-trl-grpo-vllm-colocate-completions.output_3d_bounding_scannetppv2_vllm_old_descriptionVLLM_ChartQA_splitNemotron-Personas-USA-synthetic-records-10files-qa-vllm-qwen4b-instruct-2507-clarqaQwen2.5-7B-Instruct-vllm-retriever-20251202_093826vLLM-SR-Preference-V1The files in this repo is the LLM-labeled samples that are used as the training dataset for vLLM-SR Preference model V1.
The training file (sharegpt_preference_labeld_with_negative.jsonl) contains 25k records that have sample_id, golden label for the preference-based routing policy, and a set of negative labels that are plausible but do not match the conversation context.
The validation file has the same structure, but only 1% of the training file size. The validation file and the training… See the full description on the dataset page: https://huggingface.co/datasets/ppppqp/vLLM-SR-Preference-V1.patch_tasks_vllm
Dataset Card for Patch-Based Visual Question Answering Dataset
Dataset Details
Dataset Description
This dataset contains approximately 305,000 triplets of question, answer, and image designed for patch-based visual reasoning tasks.
A standard question in this dataset is formatted as follows:
Image Grid: The image is divided into a 4x4 grid of 16 equal-sized patches. Patches are numbered sequentially from the top-left corner and moving right, then down to the… See the full description on the dataset page: https://huggingface.co/datasets/yurkes/patch_tasks_vllm.POVID_preference_data_for_VLLMsNemotron-Personas-USA-synthetic-records-10files-qa-vllm-qwen4b-instruct-2507mmluReferences: https://huggingface.co/datasets/cais/mmlu
MMLU (Vietnamese translation version)
Install
To install lm-eval from the github repository main branch, run:
git clone https://github.com/hieunguyen1053/lm-evaluation-harness
cd lm-evaluation-harness
pip install -e .
Basic Usage
Note: When reporting results from eval harness, please include the task versions (shown in results["versions"]) for reproducibility. This allows bug fixes to tasks while also… See the full description on the dataset page: https://huggingface.co/datasets/vlsp-2023-vllm/mmlu.quickstart_vllm
Dataset Card for quickstart_vllm
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/plaguss/quickstart_vllm/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/plaguss/quickstart_vllm.vllm-benchmark-payloads
vLLM Benchmark Payloads
Synthetic OpenAI-format chat-completion payloads for latency / throughput benchmarking
of a model served with vLLM's OpenAI-compatible server.
File
File
Records
Notes
payloads_1k_generic.jsonl
1,000
The benchmark dataset — one request body per line. Each has a ~12k-token system prompt + a dynamic per-record customer context.
sample_payload.json
1
One pretty-printed record, to inspect the format quickly.
All data is 100%… See the full description on the dataset page: https://huggingface.co/datasets/rohitjain28/vllm-benchmark-payloads.full_simple_online_vllm_part_3_mini_3
Dataset Card for "full_simple_online_vllm_part_3_mini_3"
More Information needed
pythia-1.4B-tldr-vllm-pair-iter-3pythia-1.4B-tldr-vllm-iter-1evalap-mfs_vllm_arena_v2-21
mfs_vllm_arena_v2 (ID: 21)
Experiment set for mfs_vllm_arena
Overview
This dataset contains 41 experiments
from the EvalAP evaluation platform.
Datasets: MFS_questions_v01
Models evaluated: google/gemma-3-27b-it, meta-llama/Llama-3.1-8B-Instruct, mistralai/Mistral-Small-3.1-24B-Instruct-2503, neuralmagic/Meta-Llama-3.1-70B-Instruct-FP8
Metrics: answer_relevancy, generation_time, judge_exactness, judge_notator, output_length
Scores… See the full description on the dataset page: https://huggingface.co/datasets/AgentPublic/evalap-mfs_vllm_arena_v2-21.openai_summarize_vllm_generated_20kpythia-1.4B-tldr-vllm-quad-iter-1deepscaler-teacher-sft-vllm-official-40k
DeepScaleR teacher SFT vLLM official 40k
Generated run: exp_003_vllm_official_brainlab_2gpu.
Summary
{
"num_examples": 40300,
"sft_dir": "data/processed/deepscaler/teacher_sft/exp_003_vllm_official_brainlab_2gpu",
"parse_rate": 0.9999751861042183,
"correct_rate": 0.5728039702233251,
"format_rate": 0.005955334987593052,
"mean_reward": 0.42432258064534184,
"deepscaler_mean_reward": 0.6266997518610422,
"deepscaler_match_mean_reward":… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.lambada_vi
Lambada (Vietnamese)
Install
To install lm-eval from the github repository main branch, run:
git clone https://github.com/hieunguyen1053/lm-evaluation-harness
cd lm-evaluation-harness
pip install -e .
Basic Usage
Note: When reporting results from eval harness, please include the task versions (shown in results["versions"]) for reproducibility. This allows bug fixes to tasks while also ensuring that previously reported scores are reproducible. See the Task… See the full description on the dataset page: https://huggingface.co/datasets/vlsp-2023-vllm/lambada_vi.summarize_from_feedback_tldr3_generated_20k_vllm_pythia1b_dpovllm_sglang_inference_deployment_triage_teaser
🚀 Cloud Infrastructure - Local LLM Inference & vLLM/SGLang Deployment Triage (Evaluation Teaser)
⚡ Official Free Evaluation Teaser (50 Verified Multi-Turn Scenarios)🏆 Get the Full Production Package (500 Samples) & Commercial EULA on Gumroad:👉 Cloud Infrastructure - Local LLM Inference & vLLM/SGLang Deployment Triage on Gumroad🏷️ Use coupon code LAUNCH20 for 20 € off at checkout!
📦 What is Inside the Full Production Package:
500 Verified FAANG v2.0… See the full description on the dataset page: https://huggingface.co/datasets/emgena/vllm_sglang_inference_deployment_triage_teaser.details_hosted_vllm__Qwen__Qwen3-8B_private
Dataset Card for Evaluation run of hosted_vllm/Qwen/Qwen3-8B
Dataset automatically created during the evaluation run of model hosted_vllm/Qwen/Qwen3-8B.
The dataset is composed of 3 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 3 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An additional… See the full description on the dataset page: https://huggingface.co/datasets/s-mizuki-nlp/details_hosted_vllm__Qwen__Qwen3-8B_private.pythia-1.4B-tldr-vllm-pair-iter-1wikipediaqa_vi
Dataset Card for "wikipedia_multi_choices"
More Information needed