Queen v5 “matriarch d20” — Crawlnet

A small language model trained from scratch. Pretraining data: pages the Crawlnet crawlers read on the crypto web (real browsers; 59% of the tokens trained), public market, funding and on-chain records written out as plain-text pages (6%), study notes a general-purpose LLM wrote for 113,078 of those pages (27%) and question/answer pairs a general-purpose LLM generated from those pages (8%); details in Pretraining data below. Tokenizer: Queen v4's, reused unchanged (trained on its crawler pages and record pages only). No pretrained weights, no FineWeb, no other corpus. Chat tuning: question/answer pairs generated by a general-purpose LLM from those pages (with the study notes' own Q&A), pairs cut from the pages and open-book conversations that answer from retrieved pages with a quote (details below).

version 5 (queen-v5)
parameters 644.9M total, 414.2M non-embedding
architecture nanochat GPT, depth 20, width 1280, 10 heads, context 2048, vocab 16384
code karpathy/nanochat @ 92d63d4e8bb4 (MIT) + crawlnet training/
dataset 310,412 pages exported 2026-10-10T20:34:46.276Z + 45,664 pages of records-v3 (exported 2026-10-06T11:30:18.157Z); after cleaning 269,164 pages: 223,537 crawler pages from 6649 domains + 45,627 record pages
dataset manifest sha256 be1297fa3c84851be7887c58d9ff594bf8ba9126ffdba6fbf39eb492452485b5; records-v3: ed71dc6d01aa9e70b26e079fcb6b42bdc12cba849a21ad9028d243deeff67c49
pretraining mix crawler pages 59%, record pages 6%, study notes written by a general-purpose LLM 27% and Q&A pairs generated by a general-purpose LLM 8% of the 2,339,400,113 tokens trained (see Pretraining data)
unique training tokens 535,128,781: crawler pages 329,274,568, record pages 22,705,121, study notes 142,834,045, generated Q&A pairs 40,315,047 (each document counted once; +6,387,763 held out)
tokens trained 2,339,373,056 = one pass over the prepared stream (4,462 steps; each document repeated by its planned passes, see Pretraining data), 5.65 tokens per non-embedding param
tokenizer BPE, 16384 tokens, Queen v4's, reused unchanged (trained on its crawler pages and record pages only)
validation loss 0.8304 bits/byte on the pages of 169 held-out sites, never trained on (pretraining; earlier versions held out other pages, so their numbers do not compare)
chat tuning (SFT) synthetic+openbook: 2,390,706 question/answer pairs generated by a general-purpose LLM from 198,882 of 381,992 page chunks (52%; crawler pages and record pages): 792,707 written for Queen v4's chat tuning and 1,597,999 from the FAQ and Q&A of the study notes (see Pretraining data), plus the pairs cut from the pages. The generator was told to use only facts on each page, and a pair whose key words are not on its page was dropped, but its wording is in this model's chat behaviour. headings: 683,478 question/answer pairs cut out of the crawler pages themselves (FAQ questions found on pages, page headings, page titles; answers are verbatim page text). No external model was used. The only human-written words are six fixed question templates such as "Tell me about {heading}." Open book (RAFT-style): 211,975 conversations built from the generated pairs, with 1-6 passages in front of the question (its own page, unless left out, and pages the site's search finds for it); the reply copies a sentence from a passage, then answers (Quote: "<sentence>" / Answer: <answer>); in 15% none of the passages holds the answer and the reply is "The pages don't say."; in 3% one passage is a copy of the source page with its key fact changed, and the reply follows the trustworthy page or says "The pages disagree." The chat tuning trained on 2,342,880 generated pairs, 211,975 open-book conversations and 683,478 headings pairs, 1 epoch.
compute 4x H100 SXM (rented), 1.272 h wall, 5.09 GPU-hours
weights this folder

Evaluation

Crypto knowledge (plain-frame log-likelihood multiple choice, acc_norm %; Queen rows are the chat-tuned releases, the other models their base checkpoints):

model cryptomc cryptoterms projectid DMind (2,874 q)
queen-v5 d20 (this model, 645M) 89.3 73.3 68.0 41.2
queen-v4 (186M) 61.3 43.3 43.5 32.3
Qwen3.5-2B-Base 46.0 66.0 31.0 31.0
SmolLM3-3B-Base 35.3 56.7 31.5 28.9
Qwen3-1.7B-Base 43.3 61.3 30.0 29.4
Qwen3.5-0.8B-Base 34.0 48.0 30.5 26.9

Every model is scored the same way: the question in a plain frame, each option's log-likelihood normalised by its length (acc_norm); 95% bootstrap intervals are about ±7 points on cryptomc/cryptoterms/projectid and ±1.7 on DMind. queen-v5 d20 vs queen-v4: better on all four, McNemar p < 0.001 each. cryptomc (150), cryptoterms (150) and projectid (200) come from crawled pages and were checked against the training data (matching documents left out); DMind (DMindAI/DMind_Benchmark objective set, 2,874 questions after removing ambiguous ones) was not part of that check, and on DMind picking the longest option scores 47.2, so treat it as a rough signal.

Reading pages from sites it never saw (400 questions about pages from 169 held-out sites (no page of those sites was trained on); the page and one page from another held-out site are put in front of the question in the model's own open-book format; % of answers holding every content word of the reference answer, and word F1):

model answer hit % F1
queen-v5 d20 (quote + answer, up to 6 passages) 68.75 0.35
queen-v4 (2-page book) 61.25 0.24

queen-v5 d20 quoted a sentence in 91% of its answers (89% verbatim in the pages) and said "The pages don't say." in 9%. Without the pages it scores 17.8% (queen-v4: 11.3%).

LLM-graded answers (the 100 fixed crypto questions of queen_train/judge_questions.json, one seeded answer each (temperature 0.7, top-k 50), graded by a general-purpose LLM: mean correctness 0-2, share fully correct, share repetitive):

model correct (0-2) fully correct % repetitive %
queen-v5 d20, with retrieved pages (closed book when the pages don't answer) 1.44 50.00 4.00
queen-v5 d20, no pages 1.53 55.00 5.00
queen-v4, with retrieved pages 1.06 23.00 8.00
queen-v4, no pages 0.86 15.00 33.00

With pages: the site's search over the crawl, as served. When queen-v5's open-book reply is "The pages don't say." (45 of 100 here: the search returned no page answering a general question) the question is asked again without pages (Queen v5's serving code does the same). Lower is better for repetitive.

Pretraining data

part what unique tokens tokens trained share
crawler pages 273,395 chunks of the crawled pages, 2-8 passes by a quality label (64,583 chunks it rated junk were not trained) 329,274,568 1,380,738,658 59.0%
record pages 45,627 record pages written from public records (8 passes), 172,974 rewordings of them (4 passes), their fields as Q&A at the end of pretraining; templates, no LLM 22,705,121 142,032,958 6.1%
study notes an explanation, an FAQ, a list of facts and entities and a Q&A list for 113,078 pages, written by a general-purpose LLM from that page; explanation, FAQ and facts 4, Q&A 6 passes 142,834,045 627,077,310 26.8%
generated Q&A pairs 964,943 question/answer pairs a general-purpose LLM generated from crawler pages and record pages for Queen v4's chat tuning, in Q&A documents: 2 passes, then regrouped in other Q&A formats at the end of pretraining 40,315,047 189,551,187 8.1%
total 535,128,781 2,339,400,113 100%

Unique tokens: every document trained at least once, counted once (with its BOS token and source line). Tokens trained: every pass of it, plus the Q&A documents regrouped for the end of pretraining. The run trained 4,462 steps of 524,288 tokens = 2,339,373,056 of the stream's 2,339,400,113.

Contributors

Queen v5 was trained on pages found by these crawlers. Owners spawned theirs by burning $CRAWLNET; the wallets are the ones that made the burn, public on-chain. Since 9 Oct 2026 every crawl.md NFT is a crawler of its own: its pages are credited to the wallet that holds the NFT (its credits name when one is set).

crawler owner pages tokens
e02 AcUm…vLRa (burn) 1,057 2,824,892
crawlzilla 3dmq…dLBC (burn) 1,180 2,502,120
ch0pper H8iW…VE3N (burn) 1,107 2,426,241
spiderman 5WKN…Meic (burn) 1,149 2,424,488
spiderman 5WKN…Meic (burn) 1,117 2,377,666
sparsity GZUQ…F59x (burn) 1,136 2,339,308
ghero6 FcEE…Cin4 (burn) 999 2,335,066
ghero5 FcEE…Cin4 (burn) 1,072 2,272,166
turtletheory ipMd…U4xb (burn) 1,059 2,268,498
ghero10 FcEE…Cin4 (burn) 1,091 2,260,444
spiderman 5WKN…Meic (burn) 1,121 2,260,069
jdubs 3v2K…GTgA (burn) 995 2,252,996
needmorecrawls 4rif…jxnZ (burn) 879 2,247,308
orb-weaver 3Zgo…wfpF (burn) 952 2,241,142
aze2 BX6f…WpEf (burn) 1,123 2,237,784
spiderman 5WKN…Meic (burn) 1,030 2,233,061
pp 3JVm…Fsm4 (burn) 1,061 2,232,237
ghero1 FcEE…Cin4 (burn) 1,073 2,219,824
redacted003 BvVr…URcY (burn) 1,132 2,213,214
ch0pper2 H8iW…VE3N (burn) 1,027 2,202,950
dash H2Lt…LbYp (burn) 1,048 2,187,760
deez CDYb…2Xxv (burn) 1,113 2,186,914
near-weaver Br2o…hHFG (burn) 1,065 2,170,368
spiderman 5WKN…Meic (burn) 1,124 2,160,363
blackandwhitedogs 2eek…pBky (burn) 1,164 2,156,238
fern 2eek…pBky (burn) 1,100 2,114,093
41n EXTV…831R (burn) 955 2,112,008
mrnakamoto 2eek…pBky (burn) 1,087 2,101,178
1gjb AyXY…HcDw (burn) 991 2,093,570
smokie 8kwY…JY7G (burn) 1,164 2,087,849
test zero…PPUT (burn) 1,175 2,079,097
wilbur 2eek…pBky (burn) 1,034 2,073,301
ghero4 FcEE…Cin4 (burn) 1,130 2,055,853
pp 3JVm…Fsm4 (burn) 1,015 2,042,977
werkle-weaver 3api…NA9T (burn) 1,005 2,041,740
onaizahparisnajd 4KZT…HerD (burn) 785 2,040,932
manylegs ETgB…wfpa (burn) 1,019 2,035,744
redacted002 BvVr…URcY (burn) 1,032 2,003,393
v4 GZUQ…F59x (burn) 1,098 1,983,034
charlotte 2eek…pBky (burn) 1,054 1,980,296
sneaky 6yNt…iikJ (burn) 971 1,977,240
e04 AcUm…vLRa (burn) 940 1,972,625
lmaocry H6GW…Hmdr (burn) 993 1,970,881
crawlzilla-2 3dmq…dLBC (burn) 929 1,966,773
ghero2 FcEE…Cin4 (burn) 999 1,945,696
007 ipMd…U4xb (burn) 917 1,940,709
littledog 2eek…pBky (burn) 1,122 1,937,464
weaver F5Vd…3hVn (burn) 1,000 1,923,618
snoopdog DRmh…ow3V (burn) 956 1,917,627
benny 36ny…e6gG (burn) 1,007 1,915,803
e05 AcUm…vLRa (burn) 937 1,906,596
web-reaper Krrc…fSaT (burn) 1,019 1,896,889
aze BX6f…WpEf (burn) 1,081 1,893,069
yancy DPXE…XNqJ (burn) 1,043 1,892,999
ruso 4rif…jxnZ (burn) 1,027 1,884,765
onepellegrino 2eek…pBky (burn) 1,005 1,883,858
addu 4gff…ksBn (burn) 842 1,879,223
weenis 36ny…e6gG (burn) 995 1,872,181
onaizahparisnajd 4KZT…HerD (burn) 818 1,870,452
ghero9 FcEE…Cin4 (burn) 1,017 1,865,507
redacted BvVr…URcY (burn) 782 1,861,941
ghero8 FcEE…Cin4 (burn) 1,005 1,859,698
canis FUy5…cjoG (burn) 884 1,857,197
page-pounder Extb…VrFG (burn) 961 1,848,770
octangone01 G64q…5PiU (burn) 949 1,840,311
e01 AcUm…vLRa (burn) 1,042 1,839,267
aze5 BX6f…WpEf (burn) 905 1,835,067
denn2 CQFL…PBVr (burn) 728 1,832,708
redacted BvVr…URcY (burn) 706 1,829,885
swolecrawls F3QF…Dfrs (burn) 1,065 1,823,712
seig 4gtD…rJMz (burn) 966 1,813,995
redacted BvVr…URcY (burn) 744 1,801,767
aspen 41CL…Q9fU (burn) 933 1,795,027
aze3 BX6f…WpEf (burn) 980 1,788,191
e03 AcUm…vLRa (burn) 917 1,787,026
kk143 8PRb…2Ufe (burn) 905 1,773,791
ghero3 FcEE…Cin4 (burn) 1,031 1,772,759
jack Diu8…atMh (burn) 994 1,761,698
elevatd 3MRp…31K7 (burn) 978 1,760,970
smokiev2 8kwY…JY7G (burn) 1,055 1,757,409
gummy 8zqX…Gv6M (burn) 784 1,746,051
callme H5y3…BR5q (burn) 739 1,739,292
mr-tenacious2 CQoH…u668 (burn) 514 1,737,508
warm 6TAx…SE4b (burn) 1,052 1,735,482
gg 4gff…ksBn (burn) 778 1,732,887
aze4 BX6f…WpEf (burn) 924 1,729,407
morelegs ETgB…wfpa (burn) 1,075 1,727,131
redacted001 BvVr…URcY (burn) 978 1,716,202
spiderman 5WKN…Meic (burn) 978 1,713,503
wei001 9ptc…3LbM (burn) 679 1,710,350
ruso-2 4rif…jxnZ (burn) 820 1,708,623
redacted BvVr…URcY (burn) 766 1,703,106
onaizahparisnajd 4KZT…HerD (burn) 721 1,699,491
chungus-spawn H7oG…CsLj (burn) 939 1,692,495
41n EXTV…831R (burn) 949 1,682,085
peterparker AbMD…52T4 (burn) 1,014 1,674,818
bigdog 2eek…pBky (burn) 1,068 1,667,649
spiderman FGyn…UuQt (burn) 1,005 1,667,474
babushka Cj9h…Cf4C (burn) 993 1,645,439
spy 8zQb…eogQ (burn) 1,000 1,628,313
onaizahparisnajd 4KZT…HerD (burn) 797 1,628,065
onaizahs-kids 4KZT…HerD (burn) 780 1,627,030
vinland 3cSP…oYeU (burn) 991 1,622,828
jeff 81Y8…GXSt (burn) 1,052 1,622,506
grand-cou FGcD…k1Dc (burn) 906 1,607,653
onaizahparisnajd 4KZT…HerD (burn) 817 1,604,063
spiderman H8iW…VE3N (burn) 1,010 1,602,702
wei004 9ptc…3LbM (burn) 686 1,599,798
cash H2Lt…LbYp (burn) 892 1,590,369
smokiev3 8kwY…JY7G (burn) 935 1,587,650
onaizah 4KZT…HerD (burn) 853 1,587,405
onaizahparisnajd 4KZT…HerD (burn) 788 1,583,635
onaizahparisnajd 4KZT…HerD (burn) 741 1,583,240
onaizahparisnajd 4KZT…HerD (burn) 817 1,580,815
redacted BvVr…URcY (burn) 765 1,580,252
oreocakester 36ny…e6gG (burn) 983 1,566,133
redacted BvVr…URcY (burn) 705 1,564,377
ghero7 FcEE…Cin4 (burn) 971 1,562,955
wakeme H5y3…BR5q (burn) 814 1,562,776
onaizahparisnajd 4KZT…HerD (burn) 777 1,541,225
onaizahparisnajd 4KZT…HerD (burn) 736 1,540,893
onaizahparisnajd 4KZT…HerD (burn) 813 1,528,690
son-of-chungus H7oG…CsLj (burn) 854 1,524,460
wei009 9ptc…3LbM (burn) 673 1,519,110
aze6 BX6f…WpEf (burn) 868 1,506,774
gigachadfuru AbMD…52T4 (burn) 948 1,506,707
redacted BvVr…URcY (burn) 782 1,502,893
goatishere2 58pZ…waHQ (burn) 793 1,499,222
9ballshooter APM9…89Nm (burn) 766 1,495,765
matrix-multiplier 6s1H…36Jg (burn) 752 1,489,270
onaizahparisnajd 4KZT…HerD (burn) 748 1,486,068
wei005 9ptc…3LbM (burn) 774 1,483,716
wei001 9ptc…3LbM (burn) 739 1,475,995
redacted BvVr…URcY (burn) 785 1,475,548
redacted BvVr…URcY (burn) 805 1,465,311
redacted BvVr…URcY (burn) 759 1,460,153
gg 4gff…ksBn (burn) 787 1,457,708
onaizahparisnajd 4KZT…HerD (burn) 727 1,448,371
creepycrawly 3v2K…GTgA (burn) 756 1,435,258
tarantula BkPa…YiMW (burn) 888 1,417,504
9ballshooter APM9…89Nm (burn) 723 1,416,477
onaizahparisnajd 4KZT…HerD (burn) 776 1,411,053
lost-again sZWt…NVmN (burn) 564 1,403,424
redacted BvVr…URcY (burn) 834 1,401,158
onaizahparisnajd 4KZT…HerD (burn) 731 1,384,550
onaizahparisnajd 4KZT…HerD (burn) 795 1,384,504
onaizahparisnajd 4KZT…HerD (burn) 704 1,374,786
redacted BvVr…URcY (burn) 800 1,365,001
history G8zB…gepY (burn) 703 1,362,113
wei008 9ptc…3LbM (burn) 638 1,361,015
neet2 8X78…cmmd (burn) 645 1,346,875
funnelweb1 DmsF…uvrF (burn) 846 1,343,823
onaizahparisnajd 4KZT…HerD (burn) 755 1,324,508
onaizahparisnajd 4KZT…HerD (burn) 742 1,321,255
redacted BvVr…URcY (burn) 800 1,299,059
gg 4gff…ksBn (burn) 750 1,291,363
wei010 9ptc…3LbM (burn) 709 1,288,932
redacted BvVr…URcY (burn) 765 1,285,682
laquisha 3v2K…GTgA (burn) 682 1,263,745
widowmaker GRjD…spY8 (burn) 739 1,257,835
wei007 9ptc…3LbM (burn) 643 1,257,336
charl0tte Ftgb…9DWW (burn) 787 1,253,428
goatishere 58pZ…waHQ (burn) 696 1,252,472
onaizahparisnajd 4KZT…HerD (burn) 693 1,249,205
onaizahskdis 4KZT…HerD (burn) 706 1,248,173
redacted BvVr…URcY (burn) 756 1,240,953
denn CQFL…PBVr (burn) 803 1,240,510
bimboboy 58pZ…waHQ (burn) 707 1,224,330
kaiyo 4gff…ksBn (burn) 781 1,211,809
onaizahparisnajd 4KZT…HerD (burn) 704 1,201,130
snaiduwa 4KZT…HerD (burn) 542 1,187,704
wei006 9ptc…3LbM (burn) 644 1,185,000
neet1 8X78…cmmd (burn) 682 1,178,465
scorpion BkPa…YiMW (burn) 474 1,162,983
wei002 9ptc…3LbM (burn) 601 1,161,626
redacted BvVr…URcY (burn) 648 1,119,157
jeff2 81Y8…GXSt (burn) 599 1,069,870
redacted BvVr…URcY (burn) 663 996,979
venom Auqo…eajz (burn) 432 993,794
mr-tenacious CQoH…u668 (burn) 517 964,400
cabbage-merchant Chhk…W6uw (burn) 455 919,322
snaiduwa 4KZT…HerD (burn) 526 907,950
amazing-grace Chhk…W6uw (burn) 459 814,668
lost sZWt…NVmN (burn) 491 779,511
crypto-scammer Chhk…W6uw (burn) 270 616,187
crawl.md #0187, #0190, #0194, #0209, #0214, #0226 +74 2PfV…gnb6 19,040 31,310,652
crawl.md #0003, #0010, #0038, #0042, #0048, #0052 +14 BvVr…URcY 4,066 7,005,545
crawl.md #0011, #0014, #0015, #0016, #0076, #0091 +4 ghero (FcEE…Cin4) 2,279 3,869,467
crawl.md #0066, #0245, #0284, #0289, #0411, #0423 +3 Cj9h…Cf4C 2,124 3,469,362
crawl.md #0022, #0127, #0144, #0166, #0833, #0893 +1 smokies (9JrE…K9du) 1,548 2,685,369
crawl.md #0189, #0213, #0355, #0365, #0528, #0639 +4 GyJV…UZVs 1,609 2,607,514
crawl.md #0142, #0299, #0434, #0459, #0553, #0769 +2 E5tZ…suX7 1,195 2,048,113
crawl.md #0329, #0375, #0852, #0882, #0892 HkWW…DEki 977 1,796,065
crawl.md #0149, #0463, #0574 zXzM…q2zW 698 1,130,015
crawl.md #0030, #0156, #0915 GhiG…3YTf 646 1,102,978
crawl.md #0480, #0506, #0598 DruL…sxJZ 722 1,098,516
crawl.md #0130, #0781, #0904 Dyr8…49zo 643 1,094,426
crawl.md #0001, #0065, #0106 58pZ…waHQ 562 1,074,763
crawl.md #0286, #0768, #0965 8VfP…iRdZ 621 960,925
crawl.md #0006, #0723 FGyn…UuQt 460 958,774
crawl.md #0019, #0023, #0024 benny (36ny…e6gG) 636 933,393
crawl.md #0036, #0040, #0087, #0102, #0124 9ptc…3LbM 484 923,705
crawl.md #0175, #0177 freedl21 (Chhk…W6uw) 447 919,985
crawl.md #0018, #0085 H5y3…BR5q 521 910,492
crawl.md #0139, #0155 ETgB…wfpa 549 907,858
crawl.md #0230, #0730 BePg…UsPk 487 874,383
crawl.md #0056, #0715, #0887 H3cP…CLfE 440 867,350
crawl.md #0060, #0163, #0940 GZUQ…F59x 496 826,439
crawl.md #0012, #0020 APM9…89Nm 456 805,250
crawl.md #0692, #0731, #0805 8NTR…JHtx 441 785,698
crawl.md #0350, #0669 5iBb…WpG7 455 774,496
crawl.md #0429, #0828, #0912 B41i…Dywj 461 688,084
crawl.md #0044, #0559 Krrc…fSaT 426 663,372
crawl.md #0533, #0563 EaY6…QWJd 352 619,915
crawl.md #0271 9ujd…YDRN 259 613,100
crawl.md #0082, #0885 9vXj…wCUM 377 608,057
crawl.md #0158, #0800 venom (Auqo…eajz) 420 605,296
crawl.md #0061, #0063, #0135, #0159, #0178 4gff…ksBn 407 566,291
crawl.md #0842 BFhn…8pBp 269 541,136
crawl.md #0673, #0742 Gvug…yd5J 349 514,105
crawl.md #0197, #0861 8e4j…sz8m 312 507,439
crawl.md #0028 widowmaker (GRjD…spY8) 250 500,266
crawl.md #0035 0x1nine84 (3Zgo…wfpF) 222 441,121
crawl.md #0101 AbMD…52T4 202 415,711
crawl.md #0582 5xxd…4Hyn 248 391,377
crawl.md #0763 CMST…9M1L 223 372,262
crawl.md #0138 scorpionking (Ftgb…9DWW) 251 364,169
crawl.md #0169 beiji (DPXE…XNqJ) 183 346,225
crawl.md #0683 themonarch (3kvL…Hi2e) 152 319,538
crawl.md #0039 grand_cou (FGcD…k1Dc) 206 296,729
crawl.md #0057 tar0ntuluh (BkPa…YiMW) 223 296,140
crawl.md #0655 auto (3Rur…3BRe) 127 295,537
crawl.md #0844 bk201 (GBwm…k3Bf) 186 291,433
crawl.md #0025 G64q…5PiU 220 288,207
crawl.md #0354 8c27…rhKt 165 285,692
crawl.md #0662 3Hua…a2hf 242 281,724
crawl.md #0059 9S69…NND6 204 277,621
crawl.md #0520 51BY…1vrb 199 275,198
crawl.md #0916 8PRb…2Ufe 156 266,918
crawl.md #0064 5TYk…wwp7 178 263,630
crawl.md #0345 fatboy (FpSm…dhqH) 150 257,441
crawl.md #0029 denn (CQFL…PBVr) 133 242,823
crawl.md #0239 GKw3…x9vJ 136 226,392
crawl.md #0999 F6TX…3sAZ 142 211,022
crawl.md #0458, #0575 5CX3…i9Mk 133 210,889
crawl.md #0323 crawly (Extb…VrFG) 178 202,508
crawl.md #0383 8p9k…bmN2 121 200,063
crawl.md #0906 95zk…FyGF 120 197,448
crawl.md #0802 param (CnnY…tB9H) 119 166,630
crawl.md #0009, #0046 EPDb…Jrxz 73 141,034
crawl.md #0602 Gmfc…s5pq 94 130,920
crawl.md #0405 4P9z…cvQS 70 95,224
crawl.md #0321 GY7a…9TNT 57 67,577
the queen's own crawlers (10) — 10,685 20,444,973

Pages and tokens count what made it into this version's dataset after cleaning and dedupe. Machine-readable: contributors.json. The 45,627 record pages (see below) were not found by a crawler and are not in this table.

What went in besides crawler pages

  • The nanochat training code, architecture and hyperparameter rules (no weights, no data).
  • Six hand-written question templates used to turn page headings into questions (see SFT above).
  • Record pages: 45,627 pages, about 10,839,462 tokens, of public market, funding and on-chain records (projects and their funding rounds, investors, token unlocks and token facts, DeFi protocols, chains and stablecoins, DEX and on-chain token statistics), written out as plain text from public data. Only factual fields were kept: no third-party labels, ratings or risk scores, and no social-media posts. They are in the pretraining data, the tokenizer and the generated chat pairs; the pairs cut from page headings use crawler pages only.
  • Study notes: a general-purpose LLM was given 113,950 crawled pages and wrote study notes from each: an explanation, an FAQ, a list of facts and entities and a Q&A list. A fact checker dropped every item with a number, address, URL or ticker that is not on its page (15,567 items); no page of a held-out site was given to it, and 5,050 notes that matched a benchmark question were left out. The notes of 113,078 pages are in the pretraining data and their FAQ and Q&A pairs in the chat tuning; their wording, and any mistake the checker could not catch, is in this model.
  • Generated Q&A pairs in pretraining: 964,943 question/answer pairs a general-purpose LLM generated from crawler pages and record pages for Queen v4's chat tuning, written as Q&A documents. 39,964 more (a fixed 2% of the questions and the earlier validation split) and 303 that matched a benchmark question never entered pretraining.
  • Chat-tuning question/answer pairs generated by a general-purpose LLM from crawler pages and record pages, with the study notes' FAQ and Q&A pairs and open-book conversations built from them (see SFT above).
  • The open-book frame of the chat tuning: two fixed replies, "The pages don't say." and "The pages disagree.", and the Quote: / Answer: reply lines.
  • Nothing else. nanochat's default SFT mixture (SmolTalk, MMLU, GSM8K) and its CORE eval were switched off.

What it says

Fixed prompts, seeded sampling (temperature 0.7, top-k 50), unedited:

What is Bitcoin?

Bitcoin is a decentralized, peer-to-peer digital currency that operates on a public network without central authorities. It is the first and most widely adopted cryptocurrency, created in 2009 by an anonymous person or group under the pseudonym Satoshi Nakamoto.

Who created Bitcoin?

Bitcoin was created by an individual or group known as Satoshi Nakamoto, who published the Bitcoin whitepaper in 2008 and released the software in 2009.

What is a blockchain?

A blockchain is a distributed ledger where transactions are recorded in chronological blocks, maintained by a network of validators who use consensus algorithms to agree on and record transactions.

Explain proof of work.

Proof of work (pronounced "woot"[1]) is a consensus algorithm for permissionless blockchains that uses mining to decide on the ledger’s state. The mining process involves performing complex calculations that require significant computational power and energy. It is designed to be difficult to produce a hash value that meets the network’s difficulty target, allowing miners to be rewarded with block rewards. The concept of Proof of Work (PoW) was first formally introduced in 1993 for the first cryptocurrency, Bitcoin.

Explain proof of stake.

The proof of stake (PoS) consensus mechanism has been around since 2012, when Sunny King and Scott Nadal created the first major cryptocurrency as a response to the energy consumption issue that PoW has had. PoS is a consensus mechanism whereby participants of the network are required to stake (lock up) or lock up (stake) coins in order to get the ability to validate transactions. Validators are chosen based on the size of their stake. The more you stake, the higher your chances of being selected as a validator.

What is Ethereum?

Ethereum is the second-largest cryptocurrency by market capitalization and the most popular blockchain platform for creating decentralized applications.

What is a smart contract?

A smart contract is a computer protocol intended for the issuance and transfer of tokens, and it is a type of blockchain application.

What is gas on Ethereum?

Gas is the unit measuring the computational work needed to execute a transaction or smart contract on Ethereum, paid for in Ether (ETH).

What is Solana?

Solana is a high-performance blockchain platform designed to support scalable applications and decentralized finance (DeFi) and other blockchain-based services.

Why is Solana fast?

Solana is fast because it is a high-throughput Layer 1 built for frequent transactions. In its typical architecture, validators process transactions in parallel and reach consensus quickly. This model allows the network to handle thousands of operations per second at low cost. The speed is further supported by Proof of History, a cryptographic clock that orders events before they reach consensus. This approach enables the network to process thousands of transactions per second without sacrificing security.

Use it

chat.py in this folder needs only karpathy/nanochat (MIT) at the commit above:

pip install torch tiktoken safetensors
git clone https://github.com/karpathy/nanochat && git -C nanochat checkout 92d63d4e8bb4
PYTHONPATH=nanochat python chat.py "What is staking?"

Or load it yourself: config.json has the nanochat GPTConfig; build nanochat.gpt.GPT, load model.safetensors; the tokenizer is tokenizer.tiktoken (tiktoken rank file) + the pattern and special tokens in tokenizer.json. Chat format: <|bos|><|user_start|>...<|user_end|><|assistant_start|>.

Limitations

Tiny model, narrow data. It makes things up, including prices, dates, addresses and links. It is not financial advice and must not be used as a source of facts.

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