datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
olmOCR_bench
Dataset Card for olmocr-bench
This is a FiftyOne dataset with 7019 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/olmOCR_bench")
# Launch the App
session = fo.launch_app(dataset)
Here is the completed dataset card, filled in… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/olmOCR_bench.tulu-v3.1-mix-preview-4096-OLMoE
OLMoE SFT Mix
The SFT mix used is an expanded version of the Tulu v2 SFT mix with new additions for code, CodeFeedback-Filtered-Instruction, reasoning, MetaMathQA, and instruction following, No Robots and a subset of Daring Anteater.
Please see the referenced datasets for the multiple licenses used in subsequent data.
We do not introduce any new data with this dataset.
Config for creation via open-instruct:
dataset_mixer:
allenai/tulu-v2-sft-mixture-olmo-4096: 1.0… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-v3.1-mix-preview-4096-OLMoE.tulu-v2-sft-mixture-olmo-2048
Dataset Card for Tulu V2 Mix (2048 OLMo version)
Note the ODC-BY license, indicating that different licenses apply to subsets of the data. This means that some portions of the dataset are non-commercial. We present the mixture as a research artifact.
This is a modified version of the Tulu V2 Mix used to train OLMo-Instruct.
The two primary differences are: long conversations are resplit into 2048-token chunks, and the hardcoded subset has been replaced with similar examples about… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture-olmo-2048.tulu-v2-sft-mixture-olmo-4096
Dataset Card for Tulu V2 Mix (4096 OLMo version)
Note the ODC-BY license, indicating that different licenses apply to subsets of the data. This means that some portions of the dataset are non-commercial. We present the mixture as a research artifact.
This is a modified version of the Tulu V2 Mix used to train newer (after April 2024) OLMo-SFT/Instruct variants (e.g. this model, or this one).
The only difference is that the hardcoded subset (dataset='hard_coded') has been replaced… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture-olmo-4096.math500-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on MATH500
This dataset contains 99 self-consistency generations per question for the
MATH500 benchmark, produced with allenai/OLMo-3-7B-Instruct at temperature
0.9, together with token-level log probabilities for each completion.
The file is intended for post-hoc analysis, self-consistency curves, adaptive
stopping, and related aggregation methods.
Source
Base benchmark: HuggingFaceH4/MATH-500
Model:… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/math500-olmo-3-7b-instruct-temp0.9-samples99-logprobs.olmo-igsm-arith
OLMo iGSM-Easy Arithmetic
This repository contains a frozen, evaluation-only release of the synthetic
mod-7 arithmetic task called iGSM-Easy Arithmetic in the accompanying OLMo
evaluation code. It contains 750 examples: 250 examples at each target depth
2, 3, and 4.
This is an i-GSM-style task variant, not a claim to be an official release
of another dataset named iGSM. The olmo-igsm-arith name is used to make the
implementation provenance explicit.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Mihara-bot/olmo-igsm-arith.mmlu-pro-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on MMLU-Pro
This dataset contains 99 self-consistency generations per question for the
MMLU-Pro test split, produced with allenai/OLMo-3-7B-Instruct at
temperature 0.9, together with token-level log probabilities for each
completion.
The file is intended for post-hoc analysis, self-consistency curves, adaptive
stopping, and related aggregation methods.
Source
Base benchmark: TIGER-Lab/MMLU-Pro
Model:… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/mmlu-pro-olmo-3-7b-instruct-temp0.9-samples99-logprobs.hotpotqa-dev-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on HotpotQA
This dataset contains 99 self-consistency generations per question for the
HotpotQA validation split, produced with allenai/OLMo-3-7B-Instruct at
temperature 0.9, together with token-level log probabilities for each
completion.
The file is intended for post-hoc analysis, self-consistency curves, adaptive
stopping, and related aggregation methods.
Source
Base benchmark: hotpotqa/hotpot_qa… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/hotpotqa-dev-olmo-3-7b-instruct-temp0.9-samples99-logprobs.popqa-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on PopQA
This dataset contains 99 self-consistency generations per question for the
PopQA benchmark, produced with allenai/OLMo-3-7B-Instruct at temperature
0.9, together with token-level log probabilities for each completion.
The file is intended for post-hoc analysis, self-consistency curves, adaptive
stopping, and related aggregation methods.
Source
Base benchmark: PopQA
Model: allenai/OLMo-3-7B-Instruct… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/popqa-olmo-3-7b-instruct-temp0.9-samples99-logprobs.