Dataset Viewer
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source
stringclasses
6 values
weight
float64
0.05
0.45
sequences
int64
9.77M
87.9M
training_tokens
int64
10B
90B
source_tokens_consumed
int64
10B
90B
sequence_length
int64
1.02k
1.02k
token_dtype
stringclasses
1 value
shards
int64
11
91
cosmopedia_v2
0.05
9,765,632
10,000,007,168
10,000,007,169
1,024
uint16
11
dclm
0.45
87,890,688
90,000,064,512
90,000,064,513
1,024
uint16
91
finemath
0.05
9,765,632
10,000,007,168
10,000,007,169
1,024
uint16
11
fineweb_edu_dedup
0.3
58,593,792
60,000,043,008
60,000,043,009
1,024
uint16
61
infiwebmath
0.05
9,765,632
10,000,007,168
10,000,007,169
1,024
uint16
11
stack_edu
0.1
19,531,264
20,000,014,336
20,000,014,337
1,024
uint16
21

TR-HASH 32K · 200B Token Mixture

Pretokenized training mixture for compact TR-HASH language-model research.

The Dataset Viewer displays one summary row per source. The actual training data is stored as packed uint16 token shards under corpora/<source>/tokens-*.bin. Each sequence contains 1,024 token IDs produced by the project 32K tokenizer.

Mixture

Source Weight Training tokens
DCLM 45% 90B
FineWeb-Edu deduplicated 30% 60B
Stack-Edu 10% 20B
FineMath 5% 10B
InfiWebMath 5% 10B
Cosmopedia v2 5% 10B

Technical manifests are stored beside each corpus. mixture_manifest.json describes the complete mixture and is not part of the Viewer split.

Models trained on this mixture

AETHORIA-AI/TR-HASH-200M-130B — 70B unique / 130B replay

This run selects a 69,992,448,000-token unique subset of the full 200B mixture, then explicitly replays selected sources for 129,984,102,400 total trained-token exposures. It does not train on the full 200B mixture.

Source Unique tokens Passes Training exposures
DCLM 19,998,965,760 1 19,998,965,760
FineWeb-Edu-Dedup 24,998,051,840 2 49,996,103,680
Stack-Edu 7,998,013,440 2 15,996,026,880
FineMath 4,999,086,080 3 14,997,258,240
InfiWebMath 4,999,086,080 3 14,997,258,240
Cosmopedia v2 6,999,244,800 2 13,998,489,600
Total 69,992,448,000 129,984,102,400

See AETHORIA-AI/TR-HASH-200M-130B for the full model card, architecture and training configuration.

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Models trained or fine-tuned on Pacific-i64/data-32k-200b-tokens