datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Nemotron-RL-Agentic-Function-Calling-Pivot-v1
Dataset Description:
This is a RL dataset for general function-calling by utilizing existing expert tool-use trajectories. We pose each assistant step of the trajectory as a separate behavior cloning problem where the policy model is incentivized to match the tool call choices of the expert model.
This dataset is released as part of NVIDIA NeMo Gym, a framework for building reinforcement learning environments to train large language models. NeMo Gym contains a growing collection of… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Function-Calling-Pivot-v1.Nemotron-RL-Agentic-Terminal-Pivot-v1
Dataset Description
The Nemotron-RL-Agentic-Terminal-Pivot-v1 dataset provides training samples for reinforcement learning of command-line ("terminal use") LLM agents with the terminus_judge environment in NeMo Gym.
Each record is a single agent decision point extracted from a successful agent trajectory on a terminal task:
responses_create_params.input — the prompt: the task instruction plus the terminal interaction history (prior agent actions and terminal outputs) up to the… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Terminal-Pivot-v1.PIVOT
PIVOT Dataset
PIVOT (Pose, Intrinsics and Viewpoint Oriented Testbed) is a multi-trajectory drone dataset designed for evaluating NeRF and 3D Gaussian Splatting under capture conditions closer to real-world robotics and autonomous systems. It provides multiple structured camera trajectories per scene together with measured sensor-based poses and COLMAP-optimized poses.
PIVOT Toolchain
The dataset is accompanied by the PIVOT GitHub repository, which… See the full description on the dataset page: https://huggingface.co/datasets/MaryRaymond/PIVOT.Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1
Dataset Description:
We created an RL dataset for conversational tool-use by utilizing existing expert tool-use trajectories. We pose each assistant step of the trajectory as a separate behavior cloning problem where the policy model is incentivized to match the tool call choices of the expert model. Each trajectory includes the use of tools for authentication, data lookup, servicing (i.e. booking reservations, changing them, getting discounts, etc), and more across 838 different… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1.PIVOT-mcap
Dataset Card for PIVOT-mcap
This is a FiftyOne dataset with 103 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/PIVOT-mcap")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/PIVOT-mcap.Nemotron-RL-Agentic-SWE-Pivot-v1
Dataset Description:
The SWE-RL dataset provides GitHub issues for training and validating real-world software engineering agents using the OpenHands environment in NeMo Gym. The dataset is a refactored version of the SWE-Gym and R2E-Gym datasets to support the NeMo Gym input format.
This dataset is released as part of NVIDIA NeMo Gym, a framework for building reinforcement learning environments to train large language models. NeMo Gym contains a growing collection of training… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-SWE-Pivot-v1.WebShop-Qwen3-8B-Adaptive-Pivot-evalWebShop-Qwen3-8B-Adaptive-Pivot-Anywin-evalWebShop-Qwen3-8B-Adaptive-Pivot2-evalWebShop-Qwen3-8B-Adaptive-Pivot-OPD-Allfail-evalWebShop-Olmo3-7B-Think-Adaptive-Pivot-8192-evalWebShop-Qwen3-8B-Adaptive-Pivot-Redistribute-evalWebShop-Olmo3-7B-Adaptive-Pivot-evalWebShop-Olmo3-7B-Adaptive-Pivot-Fenced-eval
WebShop OLMo-3-7B-Instruct pivot FENCED: held-out evaluation
WARNING: global_step_140 is the odd row out. It was produced on the NEW action parser (verl-agent commit 451b4969, which reads the action after the final </think>). It is NOT comparable to global_step_20–global_step_120, which ran on the frozen OLD-parser surface 7173787ad6e171c6 (first <action> pair anywhere). config_fingerprint does not distinguish parser surfaces, so the rows look comparable but are not. The old… See the full description on the dataset page: https://huggingface.co/datasets/wckwan/WebShop-Olmo3-7B-Adaptive-Pivot-Fenced-eval.ALFWorld-Qwen3-8B-Adaptive-Pivot-eval
ALFWorld Qwen3-8B Adaptive-Pivot: held-out evaluation
Held-out ALFWorld evaluation rows for the checkpoints in
wckwan/Alfworld-Qwen3-8B-Adaptive-Pivot
(merged_hf_actor_gs{20,40,60,80,100}; the run stopped at step 100).
Layout
global_step_N/result.json # metrics, diagnostics, task list, config, fingerprint, runtime
global_step_N/trajectories.jsonl # per-episode trajectories
global_step_N/eval_seed0.log # eval log
MANIFEST.sha256 #… See the full description on the dataset page: https://huggingface.co/datasets/wckwan/ALFWorld-Qwen3-8B-Adaptive-Pivot-eval.Alfworld-Olmo3-7B-Adaptive-Pivot-Fenced-eval
ALFWorld OLMo-3-7B-Instruct adaptive-pivot FENCED: held-out evaluation
Held-out ALFWorld evaluation rows for wckwan/Alfworld-Olmo3-7B-Adaptive-Pivot-Fenced (merged_hf_actor_gs20 through gs200, every 20 steps; the run finished at 200/200).
Layout
global_step_N/result.json # metrics, diagnostics, task list, config, fingerprint, runtime
global_step_N/trajectories.jsonl # per-episode trajectories
global_step_N/eval_seed0.log # eval log
MANIFEST.sha256… See the full description on the dataset page: https://huggingface.co/datasets/wckwan/Alfworld-Olmo3-7B-Adaptive-Pivot-Fenced-eval.WebShop-Olmo3-7B-Adaptive-Pivot-Fenced-eval-newparser
WebShop OLMo-3-7B-Instruct pivot FENCED: held-out evaluation, NEW action parser
Held-out WebShop evaluation rows for wckwan/WebShop-Olmo3-7B-Adaptive-Pivot-Fenced, steps gs140 through gs200.
NOT comparable to the gs20–gs120 rows in wckwan/WebShop-Olmo3-7B-Adaptive-Pivot-Fenced-eval. Those ran on the frozen OLD-parser surface 7173787ad6e171c6, which executes the first <action> pair anywhere in the response, including actions rehearsed and rejected inside the reasoning. These… See the full description on the dataset page: https://huggingface.co/datasets/wckwan/WebShop-Olmo3-7B-Adaptive-Pivot-Fenced-eval-newparser.Alfworld-Olmo3-7B-Adaptive-Pivot-eval
ALFWorld OLMo-3-7B-Instruct adaptive-pivot TERSE: held-out evaluation
Held-out ALFWorld evaluation rows for wckwan/Alfworld-Olmo3-7B-Adaptive-Pivot, the terse-selector control for the ALFWorld OLMo-3 pivot cell. That training run crashed at step 77, so only gs20, gs40 and gs60 exist.
Pairs with the FENCED arm in wckwan/Alfworld-Olmo3-7B-Adaptive-Pivot-Fenced-eval, evaluated on the same box, tree and protocol, for a terse-vs-fenced contrast at gs20-60.
Layout… See the full description on the dataset page: https://huggingface.co/datasets/wckwan/Alfworld-Olmo3-7B-Adaptive-Pivot-eval.glm52-datagen-r11-100-agentic-function-calling-pivot-v2-tracesdetails_maywell__PiVoT-SUS-RP
Dataset Card for Evaluation run of maywell/PiVoT-SUS-RP
Dataset automatically created during the evaluation run of model maywell/PiVoT-SUS-RP on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_maywell__PiVoT-SUS-RP.details_maywell__PiVoT-SOLAR-10.7B-RP
Dataset Card for Evaluation run of maywell/PiVoT-SOLAR-10.7B-RP
Dataset automatically created during the evaluation run of model maywell/PiVoT-SOLAR-10.7B-RP on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_maywell__PiVoT-SOLAR-10.7B-RP.details_maywell__PiVoT-10.7B-Mistral-v0.2
Dataset Card for Evaluation run of maywell/PiVoT-10.7B-Mistral-v0.2
Dataset automatically created during the evaluation run of model maywell/PiVoT-10.7B-Mistral-v0.2 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 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/open-llm-leaderboard-old/details_maywell__PiVoT-10.7B-Mistral-v0.2.WebShop-Qwen3-8B-Adaptive-Pivot-Fenced-s1000-evalWebShop-Qwen3-8B-Adaptive-Pivot-analysisNemotron-RL-Agentic-SWE-Pivot-v1-prompt-only
Nemotron-RL-Agentic-SWE-Pivot-v1-prompt-only
Prompt-only extraction from nvidia/Nemotron-RL-Agentic-SWE-Pivot-v1.
Files:
prompts.csv: one prompt extraction record per source row. Records include
prompt, separated system_prompt, and structured tools when the source row
defines available tools. Nested values are JSON-encoded inside CSV cells.
summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.
null_or_empty_rows.md: row indexes where… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Agentic-SWE-Pivot-v1-prompt-only.Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1-prompt-only
Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1-prompt-only
Prompt-only extraction from nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1.
Files:
prompts.csv: one prompt extraction record per source row. Records include
prompt, separated system_prompt, and structured tools when the source row
defines available tools. Nested values are JSON-encoded inside CSV cells.
summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1-prompt-only.Nemotron-RL-Agentic-Terminal-Pivot-v1
Dataset Description
The Nemotron-RL-Agentic-Terminal-Pivot-v1 dataset provides training samples for reinforcement learning of command-line ("terminal use") LLM agents with the terminus_judge environment in NeMo Gym.
Each record is a single agent decision point extracted from a successful agent trajectory on a terminal task:
responses_create_params.input — the prompt: the task instruction plus the terminal interaction history (prior agent actions and terminal outputs) up to the… See the full description on the dataset page: https://huggingface.co/datasets/Dabou/Nemotron-RL-Agentic-Terminal-Pivot-v1.Nemotron-RL-Agentic-Function-Calling-Pivot-v1-prompt-only
Nemotron-RL-Agentic-Function-Calling-Pivot-v1-prompt-only
Prompt-only extraction from nvidia/Nemotron-RL-Agentic-Function-Calling-Pivot-v1.
Files:
prompts.csv: one prompt extraction record per source row. Records include
prompt, separated system_prompt, and structured tools when the source row
defines available tools. Nested values are JSON-encoded inside CSV cells.
summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Agentic-Function-Calling-Pivot-v1-prompt-only.Nemotron-RL-Agentic-SWE-Pivot-v1
Dataset Description:
The SWE-RL dataset provides GitHub issues for training and validating real-world software engineering agents using the OpenHands environment in NeMo Gym. The dataset is a refactored version of the SWE-Gym and R2E-Gym datasets to support the NeMo Gym input format.
This dataset is released as part of NVIDIA NeMo Gym, a framework for building reinforcement learning environments to train large language models. NeMo Gym contains a growing collection of training… See the full description on the dataset page: https://huggingface.co/datasets/Bobollinix/Nemotron-RL-Agentic-SWE-Pivot-v1.details_maywell__PiVoT-MoE
Dataset Card for Evaluation run of maywell/PiVoT-MoE
Dataset automatically created during the evaluation run of model maywell/PiVoT-MoE on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 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.… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_maywell__PiVoT-MoE.