datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
omr_benchmark
Muse OMR Benchmark
What this is
A small, clean benchmark dataset for OMR (Optical Music Recognition — recognizing music notation from images/PDFs).
It contains 1077 pairs:
a symbolic music score (the “ground truth”, see dataset fields below)
a corresponding PDF rendering with data augmentation applied
All underlying works are Public Domain.
Why it exists
OMR is often evaluated on private or inconsistent datasets. This dataset aims to provide the community… See the full description on the dataset page: https://huggingface.co/datasets/musegroup/omr_benchmark.sets_lego_omr_full
Dataset Card for sets_lego_omr_full
This dataset combines official LEGO sets from LDRAW OMR with metadata from Rebrickable. Each entry contains the full MPD file as a string plus associated metadata such as set number, name, theme, year, and parts count. It is intended for building LLM fine-tuning datasets for LEGO model generation tasks.
Dataset Details
Dataset Sources
OMR files: LDraw OMR Library
Metadata: Rebrickable
MPD file format: LDraw File Format… See the full description on the dataset page: https://huggingface.co/datasets/DylanRiden/sets_lego_omr_full.dl-trm-phase2-codebook-v32
DL-TRM Phase 2 Codebook V32
This standalone dataset contains the Phase 2 discrete Z traces for V32.
The Hugging Face dataset viewer reads data/train.jsonl.
Each row contains:
raw_puzzle_id
route_id
route_local_id
medoid_old_id
selected_stage_a_example_index
cluster_size
vocab_size
z_trace: a length-16 list of discrete Z token IDs
The original PyTorch artifacts remain in the repo:
z_traces.pt
codebook.pt
transition_vq_model.pt
diagnostics.json
z_trace_manifest.json
checkpoints/
car_parts_datasetdl-trm-phase2-codebook-v16
DL-TRM Phase 2 Codebook V16
This standalone dataset contains the Phase 2 discrete Z traces for V16.
The Hugging Face dataset viewer reads data/train.jsonl.
Each row contains:
raw_puzzle_id
route_id
route_local_id
medoid_old_id
selected_stage_a_example_index
cluster_size
vocab_size
z_trace: a length-16 list of discrete Z token IDs
The original PyTorch artifacts remain in the repo:
z_traces.pt
codebook.pt
transition_vq_model.pt
diagnostics.json
z_trace_manifest.json
checkpoints/
dl-trm-phase2-codebook-v256
DL-TRM Phase 2 Codebook V256
This standalone dataset contains the Phase 2 discrete Z traces for V256.
The Hugging Face dataset viewer reads data/train.jsonl.
Each row contains:
raw_puzzle_id
route_id
route_local_id
medoid_old_id
selected_stage_a_example_index
cluster_size
vocab_size
z_trace: a length-16 list of discrete Z token IDs
The original PyTorch artifacts remain in the repo:
z_traces.pt
codebook.pt
transition_vq_model.pt
diagnostics.json
z_trace_manifest.json
checkpoints/
wiki2023_plus
Overview
The dataset includes the description from Wikipedia and categories of films published in 2023.
This dataset is used to evaluate the ability of LLM to memorize and extract information described in the document.
See "Where is the Answer? An Empirical Study of Positional Bias for Parametric Knowledge Extraction in Language Model (NAACL2025 Long paper)" for how we use this dataset for training and evaluation.
Data Split
film_doc_all.jsonl includes lines of… See the full description on the dataset page: https://huggingface.co/datasets/omron-sinicx/wiki2023_plus.dl-trm-phase2-codebook-v128
DL-TRM Phase 2 Codebook V128
This standalone dataset contains the Phase 2 discrete Z traces for V128.
The Hugging Face dataset viewer reads data/train.jsonl.
Each row contains:
raw_puzzle_id
route_id
route_local_id
medoid_old_id
selected_stage_a_example_index
cluster_size
vocab_size
z_trace: a length-16 list of discrete Z token IDs
The original PyTorch artifacts remain in the repo:
z_traces.pt
codebook.pt
transition_vq_model.pt
diagnostics.json
z_trace_manifest.json
checkpoints/
arc-agi-1-zloopvit-traces
ARC-AGI-1 ZLoopViT Traces
Canonical intermediate grid trajectories for all 400 training tasks in
ARC-AGI-1. Each row corresponds to one original official train or test pair;
generated augmentations are not included.
Dataset contents
400 tasks
1,718 trajectories: 1,302 demonstration/train pairs and 416 test pairs
5,059 visible intermediate transitions
Exact final-output validation on every official pair
Important columns:
task_id: official ARC task identifier… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/arc-agi-1-zloopvit-traces.AlignBench
HalCap-Bench
HalCap-Bench dataset.
Columns
model
image_source
image_name
image_type
sentence_index
caption
annotation
error_type
error_words
agreement_ratio
fleiss_Pi
n_correct
n_incorrect
n_unknown
image_url
image_path_in_repo
Notes
Notes
For COCO/CC12M items, the image is referenced by image_url.
For SD/Imagen/data_generation items, the image file is stored under images/ and referenced by image_path_in_repo.
dl-trm-phase2-controller-kmeans-v128
DL-TRM Phase 2 Controller K-Means V128
Discrete Z traces produced by k-means over Phase 1 controller deltas.
Source trace artifact: phase1_real_medoid_route_trace_shards
Input signal: medoid_controller_delta_trace[1:]
Input shape before quantization: [11400, 16, 512]
Output Z trace shape: [11400, 16]
Vocabulary size: 128
Token id base: 0
Diagnostics
{
"used_codes": 128,
"dead_codes": 0,
"perplexity": 123.55767954902056,
"unique_traces": 9222… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/dl-trm-phase2-controller-kmeans-v128.arc-agi-1-ruleloopvit-rules
ARC-AGI-1 RuleLoopViT Rules
This dataset contains one canonical, task-specific English rule for each of the
400 official ARC-AGI-1 training tasks. Rules were inferred only from official
demonstration input/output pairs. Official test inputs, test outputs, and test
traces were excluded from rule authoring.
Each row includes:
a concise standalone core_rule_text;
a five-section full_rule_text;
the corresponding structured sections;
augmentation-aware references for colors… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/arc-agi-1-ruleloopvit-rules.dl-trm-phase2-controller-kmeans-v16
DL-TRM Phase 2 Controller K-Means V16
Discrete Z traces produced by k-means over Phase 1 controller deltas.
Source trace artifact: phase1_real_medoid_route_trace_shards
Input signal: medoid_controller_delta_trace[1:]
Input shape before quantization: [11400, 16, 512]
Output Z trace shape: [11400, 16]
Vocabulary size: 16
Token id base: 0
Diagnostics
{
"used_codes": 16,
"dead_codes": 0,
"perplexity": 15.491387192451063,
"unique_traces": 9176… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/dl-trm-phase2-controller-kmeans-v16.dl-trm-phase2-controller-kmeans-v32
DL-TRM Phase 2 Controller K-Means V32
Discrete Z traces produced by k-means over Phase 1 controller deltas.
Source trace artifact: phase1_real_medoid_route_trace_shards
Input signal: medoid_controller_delta_trace[1:]
Input shape before quantization: [11400, 16, 512]
Output Z trace shape: [11400, 16]
Vocabulary size: 32
Token id base: 0
Diagnostics
{
"used_codes": 32,
"dead_codes": 0,
"perplexity": 31.17811290262774,
"unique_traces": 9191… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/dl-trm-phase2-controller-kmeans-v32.dl-trm-phase2-controller-kmeans-v256
DL-TRM Phase 2 Controller K-Means V256
Discrete Z traces produced by k-means over Phase 1 controller deltas.
Source trace artifact: phase1_real_medoid_route_trace_shards
Input signal: medoid_controller_delta_trace[1:]
Input shape before quantization: [11400, 16, 512]
Output Z trace shape: [11400, 16]
Vocabulary size: 256
Token id base: 0
Diagnostics
{
"used_codes": 256,
"dead_codes": 0,
"perplexity": 244.03568219976052,
"unique_traces": 9225… See the full description on the dataset page: https://huggingface.co/datasets/omrisap/dl-trm-phase2-controller-kmeans-v256.tiktok_trending_dishesolmo2-7b-memorized-sequences