datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
loracle-pretrain-v5-qwen14b-tokensdclm_10B_tokensERC20-Tokens-Ethereum-Cryptocurrency-Data
ERC20-Tokens-Ethereum-Cryptocurrency-Data
Hive-partitioned Parquet export of BlockDB erc20_tokens (Ethereum).
Load
from datasets import load_dataset
ds = load_dataset("BlockDB/ERC20-Tokens-Ethereum-Cryptocurrency-Data", split="train")
Files live under data/year=YYYY/month=MM/part-NNNN.parquet.
Range: 2023-08 .. 2026-06 (UTC calendar months).
Schema
column
type
block_timestamp
timestamp
block_number
int64
tx_index
int32
contract_id… See the full description on the dataset page: https://huggingface.co/datasets/BlockDB/ERC20-Tokens-Ethereum-Cryptocurrency-Data.open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-32B, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-32B.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens
Model: Qwen/Qwen3-32B
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset identifier
gpt41_mini_response
Reference response from… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8.speech-dac-tokens-3cb
Speech DAC Tokens (3 Codebooks)
Pre-tokenized speech dataset using the Descript Audio Codec (DAC). Each audio clip has been encoded into discrete codebook tokens from DAC's first 3 residual vector quantization codebooks, paired with its text transcription.
Dataset Summary
Stat
Value
Total samples
241,451
Total audio
~780 hours
Language
English
Codebooks
3 (of DAC's 9)
Codebook size
1,024 entries each
DAC model
44kHz
Tokens per second
~258 (86 frames… See the full description on the dataset page: https://huggingface.co/datasets/treadon/speech-dac-tokens-3cb.open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8
Open Thoughts 4 - Code (Qwen3-30B-A3B-Thinking-2507, 32K tokens, n=8)
This dataset contains code reasoning problems with 8 independent responses generated by Qwen3-30B-A3B-Thinking-2507.
Overview
Source: marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated (prompts only)
Model: Qwen/Qwen3-30B-A3B-Thinking-2507
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The code problem prompt
_source
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8.ru-big-russian-dataset-16k-tokens-limitmidi-tokens-dyadic-tu0.01-vb32-mts1.0-vocab512-epr-labs
midi-tokens-dyadic-tu0.01-vb32-mts1.0-vocab512-epr-labs
Pre-tokenized MIDI pieces for IsoFLOP scaling-law runs. Each row is one full
piece (no time-windowing); training crops sequences from packed token bins.
The source column is the original piece metadata as JSON so a row can be
traced back to its EPR Labs source dataset.
Based on MIDI datasets gathered by EPR Labs.
Codec
name: dyadic
tokenizer vocab size: 512
max_time_step: 1.0
n_velocity_bins: 32… See the full description on the dataset page: https://huggingface.co/datasets/wmatejuk/midi-tokens-dyadic-tu0.01-vb32-mts1.0-vocab512-epr-labs.open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-30B-A3B-Thinking-2507, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-30B-A3B-Thinking-2507.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated (base prompts)
Model: Qwen/Qwen3-30B-A3B-Thinking-2507
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8.QuRatedPajama-1B_tokens_for_analysis
QuRatedPajama
Paper: QuRating: Selecting High-Quality Data for Training Language Models
This dataset is a 1B token subset derived from princeton-nlp/QuRatedPajama-260B, which is a subset of cerebras/SlimPajama-627B annotated by princeton-nlp/QuRater-1.3B with sequence-level quality ratings across 4 criteria:
Educational Value - e.g. the text includes clear explanations, step-by-step reasoning, or questions and answers
Facts & Trivia - how much factual and trivia knowledge the text… See the full description on the dataset page: https://huggingface.co/datasets/princeton-nlp/QuRatedPajama-1B_tokens_for_analysis.open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-30B-A3B-Thinking-2507-Annotated-32768-Tokens-N8-Reformatted
Overview
This dataset is a reformatted version of marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8. The original dataset contained 29,963 samples, each with 8 responses generated by the same model with different random seeds (stored in generated_text, generated_text2, ..., generated_text8 columns). This reformatted… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-30b-a3B-thinking-2507-annotated-32768-tokens-n8-reformatted.fineweb-sample-100BT_over-1024-tokensopen-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8
Open Thoughts 4 - Math (Qwen3-4B, 32K tokens, n=8)
This dataset contains math reasoning problems with 8 independent responses generated by Qwen3-4B.
Overview
Source: marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens (n=1 version with 1 response per prompt)
Model: Qwen/Qwen3-4B
Temperature: 0.8
Max tokens: 32,768
Columns
Column
Description
instruction_seed
The math problem prompt
_source
Source dataset identifier… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens-n8.fineweb-sample-100BT_over-1024-tokens-subset-xsA subset of FineWeb sample-100BT with sequence length >= 1024 when tokenized with the Llama 2 tokenizer (including special tokens)
fineweb-sample-100BT_over-4096-tokensfineweb-sample-100BT_over-8192-tokensmidi-tokens-dyadic-tu0.01-vb32-mts1.0-vocab512-aug-lessopen-hermes-2.5-sft-mixture-llama3-inference-retrieval-tokensERC1155-Tokens-Ethereum-Cryptocurrency-Data
ERC1155-Tokens-Ethereum-Cryptocurrency-Data
Hive-partitioned Parquet export of BlockDB erc1155_tokens (Ethereum).
Load
from datasets import load_dataset
ds = load_dataset("BlockDB/ERC1155-Tokens-Ethereum-Cryptocurrency-Data", split="train")
Files live under data/year=YYYY/month=MM/part-NNNN.parquet.
Range: 2015-08 .. 2026-06 (UTC calendar months).
Schema
column
type
block_timestamp
timestamp
block_number
int64
tx_index
int32… See the full description on the dataset page: https://huggingface.co/datasets/BlockDB/ERC1155-Tokens-Ethereum-Cryptocurrency-Data.open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens-n8-reformatted
open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens
Math reasoning responses generated by Kimi K2.5 (moonshotai/Kimi-K2.5) via a Together AI dedicated instance.
Overview
Total rows: 54,920
Unique prompts: 6,865 (each with 8 response annotations)
Source prompts: marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted
Generation model: moonshotai/Kimi-K2.5
Max tokens: 32,768
Temperature: 0.8
Tokenizer used for stats: Qwen/Qwen2.5-3B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-6865-math-kimi-k2pt5-annotated-32768-tokens-n8-reformatted.open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-4B-Annotated-32768-Tokens
Overview
This dataset is a variant of the OpenThoughts-4 30K math subset with responses generated by Qwen/Qwen3-4B using max output tokens = 32768, allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-4B
Temperature: 0.8
Max Output Tokens: 32768
Dataset Statistics
Number of Samples: 29,963
Split: train
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-4b-annotated-32768-tokens.ERC721-Tokens-Ethereum-Cryptocurrency-Data
ERC721-Tokens-Ethereum-Cryptocurrency-Data
Hive-partitioned Parquet export of BlockDB erc721_tokens (Ethereum).
Load
from datasets import load_dataset
ds = load_dataset("BlockDB/ERC721-Tokens-Ethereum-Cryptocurrency-Data", split="train")
Files live under data/year=YYYY/month=MM/part-NNNN.parquet.
Range: 2023-08 .. 2026-06 (UTC calendar months).
Schema
column
type
block_timestamp
timestamp
block_number
int64
tx_index
int32… See the full description on the dataset page: https://huggingface.co/datasets/BlockDB/ERC721-Tokens-Ethereum-Cryptocurrency-Data.open-thoughts-4-30k-code-qwen3-32b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Code-Qwen3-32B-Annotated-32768-Tokens
Overview
This dataset is a variant of marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated with an extended maximum sequence length. The responses in the generated_text column were generated with max output tokens = 32768 (instead of 7500 in the original dataset), allowing for longer and more complete chain-of-thought reasoning.
Generation Details
Model: Qwen/Qwen3-32B… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-code-qwen3-32b-annotated-32768-tokens.fineweb-over-20k-l3b-tokensopen-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted-selfconsistency
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-32B-Annotated-32768-Tokens-N8-Reformatted-SelfConsistency
Overview
This dataset is a self-consistency filtered version of marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted. For each prompt, 8 responses were generated by Qwen3-32B with different random seeds. A majority vote was taken over the final answers (extracted from \boxed{...}) to determine the most popular answer, and only… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-32b-annotated-32768-tokens-n8-reformatted-selfconsistency.fineweb-sample-100BT_over-1024-tokens-subsetopen-thoughts-4-30k-math-qwen3-235b-a22b-annotated-32768-tokens
Dataset Card for Open-Thoughts-4-30K-Math-Qwen3-235B-A22B-Annotated-32768-Tokens
Overview
This dataset is a variant of marin-community/open-thoughts-4-30k-math-qwen3-235b-a22b-annotated with an extended maximum sequence length. The responses in the qwen235b_generated_text column were regenerated with max output tokens = 32768 (instead of 16000 in the original dataset), allowing for longer and more complete chain-of-thought reasoning. The conversations column has been… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/open-thoughts-4-30k-math-qwen3-235b-a22b-annotated-32768-tokens.fineweb-sample-100BT_over-2048-tokens-subsetnemotron-cc-v2.1-hq-dqa-qwen3-tokens
Nemotron-CC-v2.1 / High-Quality-DQA — tokenized with the Qwen3-8B tokenizer
Question/answer pairs extracted from nvidia/Nemotron-CC-v2.1
(High-Quality-DQA subset) and tokenized with the Qwen/Qwen3-8B tokenizer.
In the source data each row is a web document whose tail carries synthetic QA pairs marked
Question: / Answer:. Here that document is split into its original prose (context) and
the individual QA pairs, each tokenized separately. The Question: / Answer: marker keywords… See the full description on the dataset page: https://huggingface.co/datasets/jackyk02/nemotron-cc-v2.1-hq-dqa-qwen3-tokens.GPT-OSS-20B-benchmark-rollouts-512-tokens
GPT-OSS-20B Benchmark Rollouts (512 tokens)
This dataset contains text generation outputs from OpenAI's GPT-OSS-20B model across multiple evaluation benchmarks, with generation limited to 512 tokens.
Dataset Description
The dataset captures GPT-OSS-20B's text generation behavior when responding to prompts from established AI evaluation benchmarks. Each example includes the original prompt, the model's generated response, and token statistics.
Benchmark Coverage… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/GPT-OSS-20B-benchmark-rollouts-512-tokens.