datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
fineweb-tokenized
FineWeb Tokenized
> 4 trillion tokens of the pre-tokenized data the 🌐 web has to offer
What is it?
This is a pre-tokenized version of the HuggingFaceFW/fineweb dataset (currently in-progress, tokenization of the ~15 trillion tokens corpus is ongoing). The data is being pre-processed and tokenized using the AnisoleAI BPE tokenizer (52,022 vocabulary size) and packed into compact uint16 Parquet shards.
By distributing the pre-tokenized corpus, we eliminate… See the full description on the dataset page: https://huggingface.co/datasets/anisoleai/fineweb-tokenized.Claw-SWE-Bench
Claw-SWE-Bench
Paper: Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-Style Agent Harnesses on Coding Tasks
A multilingual issue-resolving benchmark with two evaluation configs:
full — 350 instances (300 from SWE-bench Multilingual + 50 Python from
SWEBench-verified-mini's size_optimized_sample).
lite — 80-instance calibrated subset (10 per language across 8
languages: Java, Go, Rust, JS/TS, C/C++, Ruby, PHP, Python). Designed for
low-cost iteration on harness… See the full description on the dataset page: https://huggingface.co/datasets/TokenRhythm/Claw-SWE-Bench.Stack_Tokenizedfineweb-tokenized-fake
What is it?
It's similar to anisolai/fineweb-tokenized but fake.
I don't understand why I did that :)
WARNING:
WHY ARE YOU DOWNLOADING IT? YOU COULD LOSE MILLIONS OF DOLLARS IF YOU USE IT TO TRAIN SOMEONE.
WHY ARE YOU DOWNLOADING IT? YOU COULD LOSE MILLIONS OF DOLLARS IF YOU USE IT TO TRAIN SOMEONE.
WHY ARE YOU DOWNLOADING IT? YOU COULD LOSE MILLIONS OF DOLLARS IF YOU USE IT TO TRAIN SOMEONE.
WHY ARE YOU DOWNLOADING IT? YOU COULD LOSE MILLIONS OF DOLLARS IF YOU USE IT TO TRAIN… See the full description on the dataset page: https://huggingface.co/datasets/mondk/fineweb-tokenized-fake.subliminal-transfer-token-replacement
Subliminal transfer: token replacement vs masking (artifacts)
Teachers, training data, per-token divergence scores and evaluation outputs for
brendanlong/subliminal-transfer-token-replacement.
The experiment asks whether replacing attribution-flagged tokens suppresses a
subliminally transmitted trait better than masking them from the loss, and
whether any advantage is specific to those tokens. Everything here is for the
one studied cell: Llama-3.2-1B-Instruct, target animal… See the full description on the dataset page: https://huggingface.co/datasets/brendanlong/subliminal-transfer-token-replacement.Scientific_Research_Tokenized
NexaSci Scientific Research Tokenized
This dataset repository now holds the active NexaSci scientific pretraining reservoir, the NexaMat controller fine-tuning pack, and archived legacy reservoir builds. The current production reservoir is the 10B-token Apache Arrow release under nexasci_reservoir_v3_10b_prod_rust/.
Current Status
The active large-scale training artifact is:
nexasci_reservoir_v3_10b_prod_rust/
It was produced from the NexaSci 10B data-engineering campaign… See the full description on the dataset page: https://huggingface.co/datasets/AethronPhantom/Scientific_Research_Tokenized.token-counts
Marin Token Counts
Token counts for all datasets used in Marin pretraining runs.
Schema
Column
Type
Description
dataset
string
Dataset identifier
marin_tokens
int
Number of tokens after tokenization
category
string
Content domain (web, code, math, academic, books, etc.)
synthetic
bool
Whether the data is LLM-generated or LLM-translated
Categories
web — Quality-classified Common Crawl text (Nemotron-CC)
code — Source code and… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/token-counts.code_x_glue_cc_code_completion_token
Dataset Card for "code_x_glue_cc_code_completion_token"
Dataset Summary
CodeXGLUE CodeCompletion-token dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/CodeCompletion-token
Predict next code token given context of previous tokens. Models are evaluated by token level accuracy.
Code completion is a one of the most widely used features in software development through IDEs. An effective code completion tool could improve software… See the full description on the dataset page: https://huggingface.co/datasets/google/code_x_glue_cc_code_completion_token.clt_gpt2_tokenized_control
Fresh multilingual GPT-2 CLT control data
Sequential, unshuffled control sample for CLT null experiments. For each language,
complete source documents were tokenized with CausalNLP/gpt2-hf_multilingual-20 at revision
0afbb31b2db3f394270d42d6a4cb7f8fceeca3d8. The first 100,000,000 tokenizer tokens were discarded
(including the complete document that crossed the threshold), after which complete
documents were retained until at least 100,000,000 tokens were collected.
Data are… See the full description on the dataset page: https://huggingface.co/datasets/abir-hr196/clt_gpt2_tokenized_control.exp-pool-repository-code-dolma2-tokenized
Locus EXP Repository Code - Dolma 2 tokenized
Pretokenized experiment pool for reproducible proxy-training runs.
MANIFEST.json is the authoritative schema, provenance, checksums, and train/holdout assignment.
shards/shard-NNNNN/tokens.bin stores little-endian int32 token IDs.
offsets.bin stores little-endian int64 document boundaries.
index.parquet stores document IDs, offsets, and compact filter fields.
metadata.parquet stores complete source metadata and is downloaded only… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/exp-pool-repository-code-dolma2-tokenized.urls-tokenized
URLs (tokenized)
ks46/urls-sampled run through a byte-level
BPE built for URLs, stored as flat uint16 token streams that memory-map
directly into a training loop.
Shards
512
URLs
18,729,786,698
Tokens
664,731,047,208
Vocabulary
8,192
Token dtype
uint16, little-endian
There is no parquet here and the dataset viewer will not render it. These
are raw token bins; see Reading the data below.
Layout
tokenizer/ the exact vocabulary… See the full description on the dataset page: https://huggingface.co/datasets/ks46/urls-tokenized.carbon-tokenized-corpus
Dataset Summary
AINovice2005/carbon-tokenized-corpus is the tokenized sample of AINovice2005/carbon-cpu-enriched-sequences-sampled .
Schema
The current dataset contains the following fields:
Field
Type
Description
record_id
string
Source/reference sequence identifier
start
int64
Start coordinate of the sequence interval
end
int64
End coordinate of the sequence interval
token_ids
list
Integer token IDs produced by the tokenizer
token_mask
list… See the full description on the dataset page: https://huggingface.co/datasets/AINovice2005/carbon-tokenized-corpus.tokenizers
Polygl0t Tokenizers
Dataset Summary
This dataset contains several subsets for training multilingual tokenizers. Every subset possesses a collection of curated text samples in different languages.
Supported Tasks and Leaderboards
This dataset can be used for the task of text generation, specifically for training and evaluating tokenizers in multiple languages.
Languages
Hindi, Bengali, English, Portuguese, and Code (a mixture of 36 programming… See the full description on the dataset page: https://huggingface.co/datasets/Polygl0t/tokenizers.african-multilingual-tokenizer-challenge
African Multilingual Tokenizer Challenge dataset
The frozen public corpus for the African Multilingual Tokenizer Challenge. It contains one balanced multilingual train split and one balanced validation split.
Split
Per language
Total
Train
40,000
240,000
Validation
4,000
24,000
Languages are English (en), French (fr), Hausa (ha), Swahili (sw), Yoruba (yo) and Amharic (am). Official public-test and private-test text are deliberately absent from this repository.… See the full description on the dataset page: https://huggingface.co/datasets/Similoluwa/african-multilingual-tokenizer-challenge.clt_gpt2_tokenized_control
Fresh multilingual GPT-2 CLT control data
Sequential, unshuffled control sample for CLT null experiments. For each language,
complete source documents were tokenized with CausalNLP/gpt2-hf_multilingual-20 at revision
0afbb31b2db3f394270d42d6a4cb7f8fceeca3d8. The first 100,000,000 tokenizer tokens were discarded
(including the complete document that crossed the threshold), after which complete
documents were retained until at least 100,000,000 tokens were collected.
Data are… See the full description on the dataset page: https://huggingface.co/datasets/CausalNLP/clt_gpt2_tokenized_control.Qwen3.8-27B-Distill-1M-3.12B-Tokens
Qwen3.8-27B-Distill-1M-4.83B-Tokens
A unified, globally deduplicated, large-scale supervised distillation corpus built from 992,318 conversations generated by Qwen/Qwen3.8-27B, containing 4,834,771,862 target output tokens (3,570,459,498 reasoning tokens + 1,264,312,364 final response tokens) and 5,104,980,053 total sequence tokens.
1. Dataset Overview
This dataset merges, aligns, and deduplicates the two primary high-quality Qwen3.8-27B generation corpora on… See the full description on the dataset page: https://huggingface.co/datasets/MaxDevv/Qwen3.8-27B-Distill-1M-3.12B-Tokens.tiny-stories-tokenized-bpecode-switching-tokenizer-robustness
Code-Switching Dataset for Tokenizer Robustness Analysis
Dataset Description
This dataset is designed for tokenizer robustness testing in multilingual and code-switching contexts. It contains identical content expressed across 16 different language variants, including pure English and 15 English-X code-switching pairs, allowing researchers to isolate tokenization effects from semantic differences when evaluating language models.
Purpose
Tokenizer Comparison:… See the full description on the dataset page: https://huggingface.co/datasets/Malikeh1375/code-switching-tokenizer-robustness.DepthBench-FineWeb-Edu-100BT-tokenized
DepthBench FineWeb-Edu 100BT Tokenized
This repository contains the tokenized FineWeb-Edu 100BT sample used by
DepthBench pretraining experiments.
Splits
train/: 139 shards, 99,585,913,529 tokens, and 97,045,608 documents.
eval/: 013_00008, containing 234,993,701 tokens and 225,078 documents.
All remaining source shards are assigned to training. Each source document is
terminated by an EOS token before documents are concatenated.
Format
Each shard… See the full description on the dataset page: https://huggingface.co/datasets/YangyiH/DepthBench-FineWeb-Edu-100BT-tokenized.midi-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.exp-pool-commit-code-dolma2-tokenized
Locus EXP Commit Code - Dolma 2 tokenized
Pretokenized experiment pool for reproducible proxy-training runs.
MANIFEST.json is the authoritative schema, provenance, checksums, and train/holdout assignment.
shards/shard-NNNNN/tokens.bin stores little-endian int32 token IDs.
offsets.bin stores little-endian int64 document boundaries.
index.parquet stores document IDs, offsets, and compact filter fields.
metadata.parquet stores complete source metadata and is downloaded only for… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/exp-pool-commit-code-dolma2-tokenized.multilingual_tokenizer_benchmark
Multilingual Tokenizer Benchmark
More details of each subset like word count, character count, original sources, etc, can be found in the dataset_meta.yaml file in the repository root.
Natural language word count functions
Download spacy models
pip install ntlk spacy pygments underthesea camel-tools
python -m spacy download ko_core_news_sm
python -m spacy download ja_core_news_sm
python -m spacy download zh_core_web_sm
import nltk
nltk.download('punkt_tab')… See the full description on the dataset page: https://huggingface.co/datasets/eduagarcia/multilingual_tokenizer_benchmark.dolma3_dolmino_megatron_tokenize
Dolma 3 / Dolmino Megatron-LM indexed dataset
This repository contains immutable Megatron-LM indexed datasets (.bin and
.idx) produced from pinned Dolma 3 and Dolmino releases. It intentionally
contains no training checkpoints, experiment outputs, logs, or dataset caches.
The indexed payloads were derived from these pinned public datasets:
allenai/dolma3_mix-150B-1025@afa92bfb22366821c5e6cd427cdd036b34b713ef… See the full description on the dataset page: https://huggingface.co/datasets/Mr-Philo/dolma3_dolmino_megatron_tokenize.exp-pool-academic-dolma2-tokenized
Locus EXP Academic - OLMo 2 tokenized
Pretokenized experiment pool for reproducible proxy-training runs.
MANIFEST.json is the authoritative schema, provenance, checksums, and train/holdout assignment.
shards/shard-NNNNN/tokens.bin stores little-endian int32 token IDs.
offsets.bin stores little-endian int64 document boundaries.
index.parquet stores document IDs, offsets, and compact filter fields.
metadata.parquet stores complete source metadata and is downloaded only for… See the full description on the dataset page: https://huggingface.co/datasets/placeholderlabs/exp-pool-academic-dolma2-tokenized.ultimate-code-tokenized
ultimate-code
Dataset Description
ultimate-code is a derived dataset built by combining and processing data from
nvidia/OpenCodeInstruct and
nvidia/OpenCodeGeneticInstruct.
It can be used to fine-tune LLMs for coding tasks.
Tokenized variant available: a pre-tokenized version of this dataset is available at
CodeForCodersYT/ultimate-code-tokenized.
Use that version if you want ready-to-train tokenized sequences instead of raw text.
Source Datasets &… See the full description on the dataset page: https://huggingface.co/datasets/CodeForCodersYT/ultimate-code-tokenized.omnimcp_cyber_token_revocation_teaser
🔬 INSPECT THE DEEPSEEK-R1 REASONING CHAIN LIVE:
Zero hallucinations. Null syntax errors. 100% AST compiler validated.🌐 Live Interactive Reasoning & Code Inspector: https://emgena.com/trainingslager🎁 Claim your Free Starter Kit (Code: STARTER100): https://emgena.com/trainingslager🏷️ Launch Discount: Get 20 € OFF any 500-incident production suite with code LAUNCH20!
📜 Enterprise Compliance: EU AI Act Articles 50 & 53 certified • 100% DSGVO / GDPR clean • Commercial EULA… See the full description on the dataset page: https://huggingface.co/datasets/emgena/omnimcp_cyber_token_revocation_teaser.subset-Itau-Unibanco-aroeira-4B-tokens
Subset Corpus Itau-Unibanco/aroeira: 1B tokens (portuguese PT-BR)
Subset Corpus Itau-Unibanco/aroeira: 1B tokens (portuguese PT-BR)
subset-Itau-Unibanco-aroeira-1B-tokens
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.token_for_AIkenGPT利用者の皆様がシャッフル・結合を行う際のために、本リポジトリ内の各フォルダ名と、対応する元のデータセットの内訳を以下にまとめます。
フォルダ名 (Folder Name)
対応する元のデータセット (Original Dataset)
ドメイン
code_5b_tokens
llm-jp-corpus-v4 (code_olmo-starcoder)
コード
en_wiki_tokens
llm-jp-corpus-v4 (en_wiki)
百科事典（英語）
fineweb_japanese
Fineweb-edu-japanese
一般Web（日本語）
fineweb-en
Fineweb-edu
一般Web（英語）
ja_kaken_tokens
llm-jp-corpus-v4 (ja_kaken)
学術・論文（日本語）
ja_patent_tokens
llm-jp-corpus-v4 (ja_patent)
特許（日本語）
ja_wiki_tokens
llm-jp-corpus-v4 (ja_wiki)
百科事典（日本語）… See the full description on the dataset page: https://huggingface.co/datasets/aoUTlum/token_for_AIkenGPT.MiniFrontier-150M-Modern-3B-token-mixture
MiniFrontier 150M-Modern 5B-token mixture
Training-mixture export from MiniFrontier - AI-LLM-Transformers-Edu-Model, an educational+modern, from-scratch decoder-only language model. Each row is one admitted document (post-filter, post-dedup, pre-tokenization) with its full provenance: text, source, revision, license, language, record_id, content_hash, path, source_type, split, parent_content_hash, transform.
License is per-example, not one blanket license for the dataset. The… See the full description on the dataset page: https://huggingface.co/datasets/igalk474/MiniFrontier-150M-Modern-3B-token-mixture.