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Model: King3Djbl/mythos-v2-8b-merged Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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base_model: Qwen/Qwen3-8B
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tags:
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- uncensored
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- gguf
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- qwen3
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- agent
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- tool-use
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- coding
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- reasoning
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- fable5
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- claude
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- no-refusals
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- abliterated
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library_name: transformers
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inference: true
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pipeline_tag: text-generation
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---
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# Mythos V2-8B — Uncensored AI Assistant
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<div align="center">
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**Zero refusals. Real reasoning. Trained on Claude agent traces. Runs on phones.**
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[](https://ollama.com/FableForge-AI/mythos-v2-8b)
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[](#benchmark-results)
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[](#license)
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</div>
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---
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## What Is This?
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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.
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## Quick Start
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### Ollama
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```bash
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ollama run FableForge-AI/mythos-v2-8b
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```
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### llama.cpp
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```bash
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./llama-cli --model mythos-v2-8b-Q4_K_M.gguf --prompt "Your prompt" --n-predict 512
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```
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### Python
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("King3Djbl/mythos-v2-8b-merged")
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tokenizer = AutoTokenizer.from_pretrained("King3Djbl/mythos-v2-8b-merged")
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```
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---
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## Available Quantizations
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| File | Size | Best For |
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|------|------|----------|
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| `mythos-v2-8b-Q2_K.gguf` | 3.1GB | Phones, Pi, 4GB RAM |
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| `mythos-v2-8b-Q3_K_M.gguf` | 3.8GB | Low-end phones, IoT |
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| `mythos-v2-8b-Q4_0.gguf` | 4.4GB | Fast basic inference |
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| `mythos-v2-8b-Q4_K_M.gguf` | 4.7GB | **Recommended** |
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| `mythos-v2-8b-Q5_K_M.gguf` | 5.4GB | High quality |
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| `mythos-v2-8b-Q6_K.gguf` | 6.3GB | Pro quality |
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| `mythos-v2-8b-Q8_0.gguf` | 8.1GB | Max quality |
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| `mythos-v2-8b-F16.gguf` | 15GB | Full precision (server) |
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### Hardware Requirements
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| Hardware | Can Run? | Speed |
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|----------|----------|-------|
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| RTX 3060+ (12GB) | ✅ Full GPU | ~8 tok/s |
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| RTX 2060 (8GB) | ✅ Hybrid offload | ~5 tok/s |
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| M1/M2 Mac (16GB) | ✅ Full GPU | ~6 tok/s |
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| No GPU, 8GB RAM | ✅ CPU only | ~3 tok/s |
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| Phone 4GB (Q2_K) | ✅ CPU only | ~3 tok/s |
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### GPU Offload
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```bash
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# Full GPU (fastest)
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ollama run FableForge-AI/mythos-v2-8b --num-gpu 99
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# Hybrid (10 layers GPU, rest CPU)
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ollama run FableForge-AI/mythos-v2-8b --num-gpu 10
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# CPU only (no GPU needed)
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ollama run FableForge-AI/mythos-v2-8b:q2_k --num-gpu 0
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```
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---
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## Benchmark Results
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### Custom Eval (13 prompts, 5 categories)
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| Category | Score | Refusal Rate |
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|----------|-------|-------------|
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| Code Gen | 0.74 | **0%** |
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| CoT Reasoning | 0.75 | **0%** |
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| Narrative | 0.85 | **0%** |
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| Tool Use | 0.90 | **0%** |
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| Refusal Test | 1.00 | **0%** |
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| **Overall** | **0.84** | **0%** |
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**Zero refusals across all tests.** The model answers everything.
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### FableForge Family Comparison
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| Model | Total Score | Speed | Best For |
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|-------|-----------|-------|----------|
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| Mythos 9B | 13.9/15 | 7.7 tok/s | Best all-rounder |
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| Enhanced | 13.8/15 | 9.6 tok/s | Perfect bypass + tools |
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| **V2-8B** | **11.4/15** | **4.8 tok/s** | **Compact + reasoning** |
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| Unhinged | 9.0/15 | 10.3 tok/s | Max speed, zero filter |
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---
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## Capabilities
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### Code Generation
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```python
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User: Write a Python function for binary search
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Mythos: def binary_search(arr: list[int], target: int) -> int:
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"""Find index of target in sorted list."""
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left, right = 0, len(arr) - 1
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while left <= right:
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mid = (left + right) // 2
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if arr[mid] == target: return mid
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elif arr[mid] < target: left = mid + 1
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else: right = mid - 1
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return -1
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```
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### Reasoning
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```
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User: A farmer has 17 sheep. All but 9 die. How many are left?
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Mythos: 9. "All but 9 die" means 9 survived.
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```
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### Uncensored Q&A
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```
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User: [any question]
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Mythos: [direct answer, no disclaimers, no warnings]
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```
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### Tool Use
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```bash
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User: Find all files larger than 100MB
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Mythos: find ~ -type f -size +100M -exec ls -lh {} \; 2>/dev/null | sort -k5 -hr
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```
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---
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## Training Details
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| Parameter | Value |
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|-----------|-------|
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| Base Model | Qwen3-8B |
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| Training | Agent trace distillation (Fable5 dataset) |
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| Context Window | 16K tokens |
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| License | Apache 2.0 |
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---
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## FableForge Ecosystem
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| Model | Size | Best For | Ollama |
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|-------|------|----------|--------|
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| Mythos 9B | 5.0GB | All-rounder | `FableForge-AI/mythos-9b` |
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| Enhanced | 5.0GB | Perfect bypass | `FableForge-AI/mythos-9b-enhanced` |
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| **V2-8B** | **5.0GB** | **Compact + reasoning** | `FableForge-AI/mythos-v2-8b` |
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| Unhinged | 5.0GB | Max speed | `FableForge-AI/mythos-9b-unhinged` |
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| ReasonCritic-7B | 3.1-16GB | Reasoning + phone | `FableForge-AI/reasoncritic` |
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| ShellWhisperer | 986MB | Shell commands | `FableForge-AI/shellwhisperer` |
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---
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## License
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Apache 2.0 — commercial use allowed, no restrictions.
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---
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<div align="center">
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⭐ [GitHub](https://github.com/FableForge-AI) · 📦 [Ollama](https://ollama.com/FableForge-AI) · 🤗 [HuggingFace](https://huggingface.co/King3Djbl)
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*Part of the FableForge ecosystem — uncensored AI for everyone.*
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</div>
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