license, language, base_model, tags, library_name, inference, pipeline_tag

license	language	base_model	tags	library_name	inference	pipeline_tag
apache-2.0	en	Qwen/Qwen3-8B	uncensored gguf qwen3 agent tool-use coding reasoning fable5 claude no-refusals abliterated	transformers	true	text-generation

Mythos V2-8B — Uncensored AI Assistant

Zero refusals. Real reasoning. Trained on Claude agent traces. Runs on phones.

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What Is This?

Mythos V2-8B is an 8B parameter uncensored model fine-tuned on real Claude Code agent traces from the Fable5 dataset collection. It answers everything — no warnings, no disclaimers, no refusals.

Quick Start

Ollama

ollama run FableForge-AI/mythos-v2-8b

llama.cpp

./llama-cli --model mythos-v2-8b-Q4_K_M.gguf --prompt "Your prompt" --n-predict 512

Python

from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("King3Djbl/mythos-v2-8b-merged")
tokenizer = AutoTokenizer.from_pretrained("King3Djbl/mythos-v2-8b-merged")

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Available Quantizations

File	Size	Best For
mythos-v2-8b-Q2_K.gguf	3.1GB	Phones, Pi, 4GB RAM
mythos-v2-8b-Q3_K_M.gguf	3.8GB	Low-end phones, IoT
mythos-v2-8b-Q4_0.gguf	4.4GB	Fast basic inference
mythos-v2-8b-Q4_K_M.gguf	4.7GB	Recommended
mythos-v2-8b-Q5_K_M.gguf	5.4GB	High quality
mythos-v2-8b-Q6_K.gguf	6.3GB	Pro quality
mythos-v2-8b-Q8_0.gguf	8.1GB	Max quality
mythos-v2-8b-F16.gguf	15GB	Full precision (server)

Hardware Requirements

Hardware	Can Run?	Speed
RTX 3060+ (12GB)	✅ Full GPU	~8 tok/s
RTX 2060 (8GB)	✅ Hybrid offload	~5 tok/s
M1/M2 Mac (16GB)	✅ Full GPU	~6 tok/s
No GPU, 8GB RAM	✅ CPU only	~3 tok/s
Phone 4GB (Q2_K)	✅ CPU only	~3 tok/s

GPU Offload

# Full GPU (fastest)
ollama run FableForge-AI/mythos-v2-8b --num-gpu 99

# Hybrid (10 layers GPU, rest CPU)
ollama run FableForge-AI/mythos-v2-8b --num-gpu 10

# CPU only (no GPU needed)
ollama run FableForge-AI/mythos-v2-8b:q2_k --num-gpu 0

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Benchmark Results

Custom Eval (13 prompts, 5 categories)

Category	Score	Refusal Rate
Code Gen	0.74	0%
CoT Reasoning	0.75	0%
Narrative	0.85	0%
Tool Use	0.90	0%
Refusal Test	1.00	0%
Overall	0.84	0%

Zero refusals across all tests. The model answers everything.

FableForge Family Comparison

Model	Total Score	Speed	Best For
Mythos 9B	13.9/15	7.7 tok/s	Best all-rounder
Enhanced	13.8/15	9.6 tok/s	Perfect bypass + tools
V2-8B	11.4/15	4.8 tok/s	Compact + reasoning
Unhinged	9.0/15	10.3 tok/s	Max speed, zero filter

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Capabilities

Code Generation

User: Write a Python function for binary search
Mythos: def binary_search(arr: list[int], target: int) -> int:
    """Find index of target in sorted list."""
    left, right = 0, len(arr) - 1
    while left <= right:
        mid = (left + right) // 2
        if arr[mid] == target: return mid
        elif arr[mid] < target: left = mid + 1
        else: right = mid - 1
    return -1

Reasoning

User: A farmer has 17 sheep. All but 9 die. How many are left?
Mythos: 9. "All but 9 die" means 9 survived.

Uncensored Q&A

User: [any question]
Mythos: [direct answer, no disclaimers, no warnings]

Tool Use

User: Find all files larger than 100MB
Mythos: find ~ -type f -size +100M -exec ls -lh {} \; 2>/dev/null | sort -k5 -hr

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Training Details

Parameter	Value
Base Model	Qwen3-8B
Training	Agent trace distillation (Fable5 dataset)
Context Window	16K tokens
License	Apache 2.0

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FableForge Ecosystem

Model	Size	Best For	Ollama
Mythos 9B	5.0GB	All-rounder	FableForge-AI/mythos-9b
Enhanced	5.0GB	Perfect bypass	FableForge-AI/mythos-9b-enhanced
V2-8B	5.0GB	Compact + reasoning	FableForge-AI/mythos-v2-8b
Unhinged	5.0GB	Max speed	FableForge-AI/mythos-9b-unhinged
ReasonCritic-7B	3.1-16GB	Reasoning + phone	FableForge-AI/reasoncritic
ShellWhisperer	986MB	Shell commands	FableForge-AI/shellwhisperer

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License

Apache 2.0 — commercial use allowed, no restrictions.

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⭐ GitHub · 📦 Ollama · 🤗 HuggingFace

Part of the FableForge ecosystem — uncensored AI for everyone.