LoafLM-10M

<p align="center"> <img src="https://huggingface.co/exnivo/LoafLM-10M/resolve/main/assets/LoafLM-Model-banner.png" alt="LoafLM — a tiny experimental cat language model" width="100%" /> </p>

LoafLM

LoafLM is a tiny experimental language model with the soul of a lazy cat.

It does not want to solve your problems.
It wants to sit on your keyboard, complain about its empty bowl, and stare at closed doors like they are a personal betrayal.

This model is small, weird, and surprisingly committed to the bit.

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What is LoafLM?

LoafLM is a 10.3M parameter causal language model trained to generate short, strange, cat-brained responses.

Its personality is built around loaf behavior:

• warm pillows
• cardboard boxes
• empty food bowls
• sunbeams
• socks
• keyboards
• dramatic reactions to closed doors

In other words:
if a housecat became a tiny language model, this would be it.

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At a Glance

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Vibe Check

LoafLM is not here to be the smartest model in the room.

LoafLM is here to say things like:

“life is a warm blanket. i sleep on it. that’s it.”

or

“i love the sunbeam. you are blocking it. move.”

or

“because the door is closed. i wanted it open. now i’m annoyed.”

That is the product.

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Recommended Generation Settings

After testing multiple temperatures, the best general setting was:

temperature = 0.4
top_k = 50
max_new_tokens = 64

Why 0.4?

Because it gave the best balance between:

• staying in character
• being weird in a good way
• not completely falling apart
• still sounding like an annoyed loaf-shaped cat

Higher temperatures get more chaotic.
Lower temperatures are a bit safer, but sometimes less funny.

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Example Outputs

Prompt

hi loaf

Output

hi. i am sitting on your keyboard. it is warm.

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Prompt

what is the meaning of life

Output

life is a warm blanket. i sleep on it. that's it.

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Prompt

tell me a joke

Output

a cat sat on a keyboard. now i'm typing on it. that's the joke.

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Prompt

do you love me

Output

i love the sunbeam. you are blocking it. move.

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Prompt

why is the door closed

Output

because the door is closed. i wanted it open. now i'm annoyed.

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GGUF: Ollama and LM Studio

The repository includes LoafLM-10M-F32.gguf, a full-precision GGUF for Ollama, LM Studio, and other llama.cpp-based applications.

LoafLM uses ReLU internally, while the stock GPT-2 runtime in llama.cpp uses GELU. The compatibility build uses a sharpened GELU transformation to closely approximate the original ReLU model without quantizing its weights. Validation against the Transformers model measured a maximum absolute logit difference of 9.03e-5, a mean difference of 8.33e-6, and 100% top-token agreement across the validation prompts. The tokenizer IDs match exactly.

Ollama

hf download exnivo/LoafLM-10M LoafLM-10M-F32.gguf --local-dir LoafLM-GGUF
hf download exnivo/LoafLM-10M Modelfile --local-dir LoafLM-GGUF
cd LoafLM-GGUF
ollama create loaflm -f Modelfile
ollama run loaflm

LM Studio

Download LoafLM-10M-F32.gguf, then import or open it in LM Studio. The GGUF already contains the tokenizer and ChatML chat template. Use a context length of 128, temperature 0.4, and top-k 50.

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Transformers Usage

LoafLM uses a custom Transformers architecture, so loading it requires trust_remote_code=True. The repository includes the model implementation and a ChatML-compatible chat template.

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "exnivo/LoafLM-10M"

tokenizer = AutoTokenizer.from_pretrained(
    model_id,
    trust_remote_code=True,
)

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    trust_remote_code=True,
    dtype=torch.float32,
).eval()

messages = [
    {"role": "user", "content": "what is the meaning of life"}
]

prompt = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True,
)
inputs = tokenizer(prompt, return_tensors="pt")

with torch.inference_mode():
    output = model.generate(
        **inputs,
        max_new_tokens=64,
        temperature=0.4,
        top_k=50,
        do_sample=True,
    )

new_tokens = output[0, inputs["input_ids"].shape[1]:]
print(tokenizer.decode(new_tokens, skip_special_tokens=True))

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What LoafLM Is Good At

LoafLM is surprisingly decent at:

• short funny replies
• staying on a cat theme
• silly personality responses
• light meme interactions
• being small and cute
• acting like it has better things to do

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What LoafLM Is Bad At

LoafLM is bad at:

• serious reasoning
• reliable coding
• factual accuracy
• long coherent writing
• useful assistance
• being normal

If you ask it for Python code, it may decide that your bowl is empty and that this is now the main issue.

That is expected behavior.

---

Temperature Test Summary

A quick temperature sweep showed:

Conclusion:

0.4 is the recommended default. Still, if you want pure chaos, go higher and accept the consequences.

---

Intended Use

LoafLM is intended for:

• meme projects
• tiny model experiments
• personality model testing
• funny chatbot demos
• “what if a cat was an LLM?” research
• making your friends ask “why does this exist?”

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Not Intended For

LoafLM is not intended for:

• medical advice
• legal advice
• financial advice
• serious coding help
• schoolwork
• truth
• wisdom
• stability
• any mission-critical task
• open-door policy enforcement

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Limitations

LoafLM is extremely small and very experimental.

It may:

• repeat itself
• ignore the prompt
• drift into nonsense
• become too obsessed with pillows
• act hungry at inappropriate times
• forget what it was doing
• produce weak prompt matches
• hallucinate
• loaf

This is not a bug.
This is part of the loaf stack.

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Training Philosophy

LoafLM was not built to compete with serious models.

It was built because tiny weird models are fun.

The goal was simple:

make a model that feels like a mildly rude cat sitting in your house.

If it gives you one amazing response and then immediately says something stupid about a sock, that means it is working.

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TL;DR

LoafLM is:

• tiny
• funny
• cat-coded
• weirdly charming
• not useful in the traditional sense
• spiritually located on a warm pillow

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Final Warning

If you use this model, understand the risks:

• it may judge you
• it may refuse to care
• it may prioritize a sunbeam over your prompt
• it may emotionally side with the cat

You have been warned.