nanoBeard Sloop 14M (pirate, GPT-2)

GGUF quantizations of nanoBeard Sloop โ€” a tiny 14M GPT-2-style pirate text model (completion, no chat turns), loaded via llama.cpp's gpt2 arch (14M params), for on-device inference with llama.cpp and the NanoBeard mobile app. Val loss โ‰ˆ 4.282.

Files

file quant size use
sloop-14M.Q4_K_M.gguf Q4_K_M 11.1 MB default โ€” phones
sloop-14M.Q8_0.gguf Q8_0 14.7 MB quality fallback

Q4_K_M is the default for phones (smallest + fastest). Q8_0 is a near-lossless fallback when you have the storage and want max quality.

Chat format

Plain-text turns (no chat template). Build the prompt as:

User: <your message>
Pirate:

Turns are separated by a single newline; stop generation at the <|endoftext|> token. Example with llama.cpp:

llama-completion -m sloop-14M.Q4_K_M.gguf \
  -p $'User: Tell me about the sea.\nPirate:' -n 80 --temp 0.8 --top-k 40

Tokenizer

Custom 16,384-token byte-level BPE (GPT-2-style pre-tokenizer), embedded in the GGUF. No external tokenizer file required.

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Model size
13.9M params
Architecture
gpt2
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