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grenishrai/yoru-GGUF overview

Yoru yoru 1.7b.png Yoru GGUF Yoru is a model in the Mori family. This repo is the Q4 K M GGUF of the merged F16 checkpoint grenishrai/yoru https://huggingface.…

ggufquantizedllamaconversationalchatslanggen-zsmollm2moriyorutext-generationendataset:grenishrai/genz-sft-datasetbase_model:grenishrai/yorubase_model:quantized:grenishrai/yorulicense:mitendpoints_compatibleregion:us

Runs locally from ~1006.7 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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yoru-Q4_K_M.ggufGGUFQ4_K_M1006.7 MBDownload

Model Details

Model IDgrenishrai/yoru-GGUF
Authorgrenishrai
Pipelinetext-generation
Licensemit
Base modelgrenishrai/yoru
Last modified2026-08-14T10:24:54.000Z

Model README

---

license: mit

pretty_name: Yoru GGUF

language:

- en

base_model: grenishrai/yoru

base_model_relation: quantized

library_name: gguf

pipeline_tag: text-generation

tags:

- gguf

- quantized

- llama

- conversational

- chat

- slang

- gen-z

- smollm2

- mori

- yoru

datasets:

- grenishrai/genz-sft-dataset

---

!Yoru

Yoru GGUF

Yoru is a model in the Mori family. This repo is the Q4_K_M GGUF of the merged F16 checkpoint grenishrai/yoru.

Use this file with llama.cpp, LM Studio, Ollama, or any GGUF runner. For Transformers / PEFT, use the F16 repo instead.

It is a style / persona mix for casual internet / Gen Z chat, not a facts model.

Model Details

| File | Type | Size | Notes |

| --- | --- | ---: | --- |

| yoru-Q4_K_M.gguf | Q4_K_M | ~1.06 GB | only file in this repo; default |

The F16 source is ~3.42 GB. This quant is the shareable / local-inference copy.

How to Use

Pass the same system prompt the data used, or the voice will slip.

You are a pure Gen Z speaker. Always reply in natural Gen Z slang and internet speech. Use words and phrases like: no cap, fr fr, lowkey, highkey, bet, rizz, mid, slay, periodt, it's giving, sus, oof, vibes, down horrendous, bussin, cooked, goated, main character, etc. Keep replies casual, short to medium length, and online. Never break character. Never explain the slang. Never sound formal or like a normal AI.

llama.cpp

llama-cli -hf grenishrai/yoru-GGUF \
  --sys "You are a pure Gen Z speaker. Always reply in natural Gen Z slang and internet speech. Use words and phrases like: no cap, fr fr, lowkey, highkey, bet, rizz, mid, slay, periodt, it's giving, sus, oof, vibes, down horrendous, bussin, cooked, goated, main character, etc. Keep replies casual, short to medium length, and online. Never break character. Never explain the slang. Never sound formal or like a normal AI." \
  -p "I barely slept and now I have to be a person today"

Local file:

llama-cli -m yoru-Q4_K_M.gguf \
  --sys "You are a pure Gen Z speaker. ..." \
  -p "I barely slept and now I have to be a person today"

LM Studio / Ollama

Import yoru-Q4_K_M.gguf. Set the chat template to ChatML if it is not picked up from the GGUF. Put the system prompt above in the system field.

Python (llama-cpp-python)

from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="grenishrai/yoru-GGUF",
    filename="yoru-Q4_K_M.gguf",
    n_ctx=8192,
)

system = (
    "You are a pure Gen Z speaker. Always reply in natural Gen Z slang and internet speech. "
    "Use words and phrases like: no cap, fr fr, lowkey, highkey, bet, rizz, mid, slay, periodt, "
    "it's giving, sus, oof, vibes, down horrendous, bussin, cooked, goated, main character, etc. "
    "Keep replies casual, short to medium length, and online. Never break character. "
    "Never explain the slang. Never sound formal or like a normal AI."
)

out = llm.create_chat_completion(
    messages=[
        {"role": "system", "content": system},
        {"role": "user", "content": "I barely slept and now I have to be a person today"},
    ],
    max_tokens=80,
    temperature=0.8,
    top_p=0.9,
)
print(out["choices"][0]["message"]["content"])

Uses

Same as the F16 model: short informal chat, persona experiments. Not for formal, medical, legal, or factual QA. Not a sample of real Gen Z speech.

Q4_K_M will be a bit less sharp than F16. If a reply looks off, check the same prompt on grenishrai/yoru before blaming the fine-tune.

Training / quant

Yoru was QLoRA-trained on SmolLM2-1.7B-Instruct, best checkpoint epoch 2, then merged to fp16. This file is that merge quantized with llama.cpp Q4_K_M. Training details live on the F16 card.

Citation

@misc{yoru-gguf-2026,
  title  = {Yoru (Mori) Q4_K_M GGUF},
  author = {grenishrai},
  year   = {2026},
  url    = {https://huggingface.co/grenishrai/yoru-GGUF},
  note   = {Quantized from https://huggingface.co/grenishrai/yoru}
}

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