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simpledirect/Vinci-Piccolo-1.0-GGUF overview

<p align="center" Vinci https://vinci assets.s3.ca central 1.amazonaws.com/Vinci/logo+design/PNG/hf dark logo.png hf light mode only Vinci https://vinci assets…

ggufquantizedqwen3_5conversationalchatcharactersimpledirectvincitext-generationbase_model:simpledirect/Vinci-Piccolo-1.0base_model:quantized:simpledirect/Vinci-Piccolo-1.0license:apache-2.0endpoints_compatibleregion:us

Runs locally from ~2.52 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

3 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
vinci-piccolo-1.0-20260629-Q4_K_M.ggufGGUFQ4_K_M2.52 GBDownload
vinci-piccolo-1.0-20260629-Q5_K_M.ggufGGUFQ5_K_M2.86 GBDownload
vinci-piccolo-1.0-20260629-Q6_K.ggufGGUFQ6_K3.23 GBDownload

Model Details

Model IDsimpledirect/Vinci-Piccolo-1.0-GGUF
Authorsimpledirect
Pipelinetext-generation
Licenseapache-2.0
Base modelsimpledirect/Vinci-Piccolo-1.0
Last modified2026-06-29T21:38:26.000Z

Model README

---

base_model: simpledirect/Vinci-Piccolo-1.0

library_name: gguf

pipeline_tag: text-generation

tags:

- gguf

- quantized

- qwen3_5

- conversational

- chat

- character

- simpledirect

- vinci

license: apache-2.0

widget:

  • messages:

- role: user

content: "What's a hard truth I need to hear?"

  • messages:

- role: user

content: "Who are you?"

---

<p align="center">

!Vinci

!Vinci

</p>

Vinci Piccolo 1.0 — GGUF

GGUF (quantized) builds of Vinci Piccolo, for local inference with Ollama, LM Studio, and llama.cpp. For the full-precision weights, evals, and details, see simpledirect/Vinci-Piccolo-1.0.

Available variants

| File | Size | Min RAM | Notes |

|---|---|---|---|

| vinci-piccolo-1.0-20260629-Q6_K.gguf | 3.46 GB | 12 GB | Closest to BF16 quality |

| vinci-piccolo-1.0-20260629-Q5_K_M.gguf | 3.07 GB | 10 GB | Good balance (recommended) |

| vinci-piccolo-1.0-20260629-Q4_K_M.gguf | 2.71 GB | 8 GB | Smallest, tight memory budgets |

GPU: Q5_K_M and Q4_K_M run on 4 GB VRAM; Q6_K needs 6 GB. Mac M-series: Q5_K_M fits on 8 GB unified memory; Q6_K needs 16 GB.

Ollama

ollama run hf.co/simpledirect/Vinci-Piccolo-1.0-GGUF

llama.cpp

./llama-cli \
    -m vinci-piccolo-1.0-20260629-Q5_K_M.gguf \
    --ctx-size 262144 \
    --temp 0 \
    --chat-template qwen3

llama-server (OpenAI-compatible API)

./llama-server \
    -m vinci-piccolo-1.0-20260629-Q5_K_M.gguf \
    --ctx-size 262144 \
    --host 0.0.0.0 \
    --port 8080

Prompt format

Qwen / ChatML chat template. No system prompt required — character is trained into the weights. Pass enable_thinking=False when using the tokenizer directly to suppress <think> output.

Citation

@misc{simpledirect2026vinci,
  title        = {Vinci Piccolo 1.0},
  author       = {{SimpleDirect}},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/simpledirect/Vinci-Piccolo-1.0}},
  note         = {Apache 2.0. Fine-tuned from Qwen/Qwen3.5-4B.},
}

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