Queen v1 “hatchling” — Crawlnet
A small language model trained from scratch. Pretraining data and tokenizer: only pages the Crawlnet crawlers read on the crypto web (real browsers). No pretrained weights, no FineWeb, no other corpus. Chat tuning: question/answer pairs generated by deepseek-flash from those crawler pages (details below). Expect a dumb, funny, confidently-wrong model; that is the point.
| version | 1 (queen-v1) |
| parameters | 42.1M total, 16.9M non-embedding |
| architecture | nanochat GPT, depth 6, width 384, 6 heads, context 1024, vocab 16384 |
| code | karpathy/nanochat @ 92d63d4e8bb4 (MIT) + crawlnet training/ |
| dataset | 10,521 pages exported 2026-10-04T08:42:35.913Z; after cleaning 10,518 pages, 392 domains |
| dataset manifest sha256 | 1258202cf03b6202c5c69112d5a82a34ac6d9d3cb9175fb92282ff4ebea64e32 |
| unique training tokens | 20,758,910 (+160,122 held out) |
| tokens trained | 82,837,504 = 3.99 epochs, 4.9 tokens per non-embedding param |
| tokenizer | BPE, 16384 tokens, trained on the same crawler pages only |
| validation loss | 1.5162 bits/byte on held-out crawler pages (pretraining) |
| chat tuning (SFT) | synthetic:deepseek-flash: 14,933 question/answer pairs generated by deepseek-flash (DeepSeek-V4.1-Flash (open weights, MIT license; DeepSeek API terms 4.2(3) allow training other models on outputs), via api.deepseek.com) from 5,000 crawler pages, plus the pairs cut from the pages. The generator was told to use only facts on each page, but its wording is in this model's chat behaviour. headings: 60,562 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}." |
| compute | 1 GPU (our GPU server), 0.168 h wall, 0.168 GPU-hours |
| cost | $0.06 GPU + ~$2.26 deepseek-flash API for the chat-tuning pairs (list price) |
| weights | https://huggingface.co/Crawlnet/queen-v1 |
Contributors
Queen v1 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.
| crawler | owner | pages | tokens |
|---|---|---|---|
| v4 | GZUQ…F59x (burn) |
192 | 496,732 |
| littledog | 2eek…pBky (burn) |
194 | 440,607 |
| ghero4 | FcEE…Cin4 (burn) |
153 | 429,198 |
| ghero5 | FcEE…Cin4 (burn) |
138 | 428,844 |
| spiderman | 5WKN…Meic (burn) |
203 | 425,019 |
| mrnakamoto | 2eek…pBky (burn) |
192 | 410,263 |
| aze | BX6f…WpEf (burn) |
190 | 401,801 |
| spiderman | 5WKN…Meic (burn) |
170 | 380,647 |
| near-weaver | Br2o…hHFG (burn) |
149 | 377,785 |
| crawlzilla | 3dmq…dLBC (burn) |
174 | 372,907 |
| spiderman | 5WKN…Meic (burn) |
154 | 371,033 |
| ruso | 4rif…jxnZ (burn) |
169 | 362,160 |
| sparsity | GZUQ…F59x (burn) |
188 | 357,951 |
| bigdog | 2eek…pBky (burn) |
161 | 337,956 |
| test | zero…PPUT (burn) |
218 | 331,261 |
| blackandwhitedogs | 2eek…pBky (burn) |
162 | 330,107 |
| swolecrawls | F3QF…Dfrs (burn) |
162 | 316,290 |
| deez | CDYb…2Xxv (burn) |
192 | 314,699 |
| ghero7 | FcEE…Cin4 (burn) |
136 | 304,677 |
| ghero9 | FcEE…Cin4 (burn) |
134 | 300,943 |
| spiderman | 5WKN…Meic (burn) |
172 | 297,870 |
| ghero2 | FcEE…Cin4 (burn) |
126 | 291,399 |
| smokie | 8kwY…JY7G (burn) |
155 | 288,743 |
| aze2 | BX6f…WpEf (burn) |
158 | 280,718 |
| onepellegrino | 2eek…pBky (burn) |
145 | 273,017 |
| spiderman | 5WKN…Meic (burn) |
147 | 267,490 |
| ghero3 | FcEE…Cin4 (burn) |
123 | 261,159 |
| charlotte | 2eek…pBky (burn) |
150 | 252,818 |
| ghero6 | FcEE…Cin4 (burn) |
109 | 250,745 |
| spiderman | H8iW…VE3N (burn) |
167 | 250,232 |
| warm | 6TAx…SE4b (burn) |
123 | 249,392 |
| ch0pper | H8iW…VE3N (burn) |
123 | 249,313 |
| fern | 2eek…pBky (burn) |
153 | 246,142 |
| wilbur | 2eek…pBky (burn) |
135 | 243,970 |
| babushka | Cj9h…Cf4C (burn) |
138 | 243,091 |
| ghero8 | FcEE…Cin4 (burn) |
111 | 224,138 |
| ghero1 | FcEE…Cin4 (burn) |
134 | 222,999 |
| lmaocry | H6GW…Hmdr (burn) |
110 | 218,530 |
| ghero10 | FcEE…Cin4 (burn) |
112 | 210,962 |
| ch0pper2 | H8iW…VE3N (burn) |
115 | 208,241 |
| yancy | DPXE…XNqJ (burn) |
109 | 207,054 |
| dash | H2Lt…LbYp (burn) |
100 | 192,604 |
| jeff | 81Y8…GXSt (burn) |
115 | 188,852 |
| manylegs | ETgB…wfpa (burn) |
114 | 183,661 |
| spiderman | 5WKN…Meic (burn) |
86 | 180,939 |
| jdubs | 3v2K…GTgA (burn) |
62 | 171,264 |
| vinland | 3cSP…oYeU (burn) |
61 | 170,127 |
| gigachadfuru | AbMD…52T4 (burn) |
96 | 168,825 |
| jack | Diu8…atMh (burn) |
82 | 168,503 |
| redacted002 | BvVr…URcY (burn) |
94 | 165,985 |
| weaver | F5Vd…3hVn (burn) |
80 | 162,320 |
| seig | 4gtD…rJMz (burn) |
67 | 159,469 |
| pp | 3JVm…Fsm4 (burn) |
81 | 159,331 |
| werkle-weaver | 3api…NA9T (burn) |
100 | 157,605 |
| pp | 3JVm…Fsm4 (burn) |
78 | 151,260 |
| redacted003 | BvVr…URcY (burn) |
65 | 147,573 |
| weenis | 36ny…e6gG (burn) |
87 | 147,478 |
| oreocakester | 36ny…e6gG (burn) |
73 | 145,266 |
| morelegs | ETgB…wfpa (burn) |
70 | 142,642 |
| elevatd | 3MRp…31K7 (burn) |
70 | 142,065 |
| smokiev2 | 8kwY…JY7G (burn) |
85 | 141,041 |
| peterparker | AbMD…52T4 (burn) |
82 | 132,506 |
| web-reaper | Krrc…fSaT (burn) |
81 | 130,175 |
| redacted001 | BvVr…URcY (burn) |
63 | 121,647 |
| spiderman | FGyn…UuQt (burn) |
62 | 118,440 |
| turtletheory | ipMd…U4xb (burn) |
53 | 107,294 |
| benny | 36ny…e6gG (burn) |
81 | 94,983 |
| cash | H2Lt…LbYp (burn) |
40 | 85,927 |
| grand-cou | FGcD…k1Dc (burn) |
42 | 56,797 |
| spy | 8zQb…eogQ (burn) |
24 | 49,975 |
| the queen's own crawlers (6) | — | 2,078 | 3,778,418 |
Pages and tokens count what made it into this version's dataset after cleaning and dedupe. Machine-readable: contributors.json.
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).
- Chat-tuning question/answer pairs generated by
deepseek-flashfrom crawler pages (see SFT above). - 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/top-k in samples.json), unedited:
What is Bitcoin?
Bitcoin is a peer-to-peer cash system that allows users to send transactions and earn rewards by sending them to a peer-to-peer network. It is a set of cryptocurrencies that are used to run a smart contract, a smart contract.
Who created Bitcoin?
Bitcoin is created by Satoshi Nakamoto. Bitcoin holders have the potential to be the most trusted person or person in the world. Bitcoin is named after the pseudonym of Satoshi Nakamoto.
What is a blockchain?
A blockchain is a system that is designed for use with decentralized applications (dApps). It is the foundation, not the underlying infrastructure. A blockchain has its own consensus layer, and has to be the most used method to execute decentralized applications.
Explain proof of work.
Proof of work (RPOW) is an important element of a set of consensus changes that can be applied to bitcoin as transactions by only new bitcoin. Although the set of new transactions, this is not the only way to solve the consensus problem. The rest of the work of a single set of transactions must be recorded sequentially as before a previous block. Bitcoin is the process of creating transactions and computing a new one.
Explain proof of stake.
The proof producer generates a new key in the validator’s pubkey. The validator’s public key is determined by the validator’s pubkey. The new DelegationContract represents the total stake of a validator’s public key, and the associated stake is allocated to a new validator. The new key, the new public key, and the new key is added to the validator’s pubkey as a stake, which is the address of the new validator’s private key. The new key is a new validator key, and the new key is added to the new key. It is added to the new validator key, allowing for
What is Ethereum?
A Bitcoin blockchain is a decentralized digital currency that uses cryptography to secure transactions and transactions. It is used to provide a blockchain ledger that acts as a peer-to-peer network. This is how digital assets are stored and secured and managed using a peer-to-peer network.
What is a smart contract?
A smart contract is a smart contract that allows users to create tokens that can be transferred between a specific contract and a specific amount of a predefined contract. The smart contract is a smart contract that manages the logic of a smart contract. A smart contract can also have extensive permissions' permissions, including the smart contract code.
What is gas on Ethereum?
Ethereum is a decentralized application platform that allows developers to create decentralized applications (dapps) that build decentralized apps that can benefit from Ethereum's development and compatibility.
What is Solana?
Solana is a blockchain built by the Solana network. The blockchain is a computer that connects to Solana and is fully the decentralized network of nodes and nodes on the Solana network. Solana is a blockchain platform that is used to run decentralized applications (dapps) and smart contracts. It is used to provide a smart contract that powers certain types of applications and assets. Solana is the leading blockchain-based cryptocurrency that powers Solana.
Why is Solana fast?
Solana is fast, fast, and cost-effective, fast, efficient, and cost-effective solutions.
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.