Files

ModelHub XC a5cdbdbcc5 初始化项目，由ModelHub XC社区提供模型

Model: SynastriaNetworks/OpenFable-4B
Source: Original Platform

2026-06-24 12:11:16 +08:00

4.0 KiB

Raw Permalink Blame History

base_model, tags, license, language

base_model

OpenFable-4B

"The US banned Fable 5 outside America. I'm outside America. So I made my own."

OpenFable-4B is a fine-tune of Qwen3-4B designed to replicate the conversational style, reasoning depth, and structured output quality of Claude Fable 5 — built entirely from scratch by a solo developer in Brazil.

This is not a generic instruction-tuned model. It's a deliberate attempt to bring Fable-style responses to the open-source ecosystem, with a custom-built dataset and a personality baked into the chat template.

What makes it different

Style-first fine-tune — trained to match Claude Fable 5's tone: direct, warm, structured, and non-verbose
Custom dataset — ~300 hand-curated examples across coding, math, agentic planning, and cybersecurity. No public synthetic datasets that leak CoT preambles
Custom chat template — default system prompt embedded in tokenizer_config.json: "You are OpenFable, created by SynastrIA Networks"
GGUF quantized — Q4_K_M, ready for local inference via llama.cpp, LM Studio, PocketPal, or Jan

Benchmarks

MMLU — Zero-shot (no few-shot)

OpenFable-4B was evaluated on MMLU with zero-shot prompting, achieving an overall score of 68.48%.

Strongest in Social Sciences. Weakest in Humanities — expected given the dataset skew toward technical and reasoning tasks.

GSM8K — Comparison with 4B-class models

OpenFable-4B holds its own against the competitive 4B landscape on grade-school math reasoning:

OpenFable matches top-tier 4B models on math reasoning despite being a style fine-tune, not a reasoning-optimized model. The base Qwen3-4B it's built on scores ~76% — OpenFable closes that gap significantly through LoRA training.

Model details

Property	Value
Base model	Qwen/Qwen3-4B
Fine-tuning method	LoRA (via Unsloth)
Dataset size	~300 examples
Quantization	Q4_K_M (GGUF)
Context length	32768
Language	English
License	Apache 2.0

Usage

llama.cpp

./llama-cli \
  -m OpenFable-4B-Q4_K_M.gguf \
  -p "You are OpenFable, created by SynastrIA Networks." \
  --ctx-size 4096 \
  -i

Python (llama-cpp-python)

from llama_cpp import Llama

llm = Llama(
    model_path="OpenFable-4B-Q4_K_M.gguf",
    n_ctx=4096,
    chat_format="chatml",
)

response = llm.create_chat_completion(
    messages=[
        {"role": "system", "content": "You are OpenFable, created by SynastrIA Networks."},
        {"role": "user", "content": "Explain how LoRA fine-tuning works."},
    ]
)

print(response["choices"][0]["message"]["content"])

LM Studio / Jan / PocketPal

Download the .gguf file and load it directly. The system prompt is already embedded in the tokenizer config — no manual setup required.

Downloads

Format	Link
GGUF (Q4_K_M)	gustajunq/OpenFable-4B-GGUF
Org page	SynastrIA Networks on HuggingFace

Known limitations

Humanities performance lags behind other categories (~59.5% MMLU) — reflective of dataset composition
Style fine-tune, not RLHF-aligned — may occasionally drift on edge-case prompts
Not optimized for multilingual use — English only

About

Built by Gustavo at SynastrIA Networks — a one-person AI startup from Brazil.

OpenFable is part of the broader SynastrIA ecosystem, which includes Lucian, an AI agent platform for creators.

Follow the build-in-public journey: @synastriadev · @openfable

V2 — June 2026

4.0 KiB Raw Permalink Blame History