Instructions to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Use Docker

docker model run hf.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Ollama
How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with Ollama:
```
ollama run hf.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
```
Unsloth Desktop

How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with Docker Model Runner:
```
docker model run hf.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
```

Lemonade

How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwythos-9B-Claude-Mythos-5-1M-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

empero-ai commited on Jul 12

Commit

50d8b30

verified ·

1 Parent(s): a7ab0f6

Update README.md

Browse files

Files changed (1) hide show

README.md +14 -10

README.md CHANGED Viewed

@@ -23,28 +23,32 @@ tags:
 - agentic
 ---
-<p align="center">
-  <img src="https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M/resolve/main/assets/qwythos.png" alt="Qwythos-9B" width="640"/>
-</p>
 <table>
 <tr>
 <td>
-## 🚨 v3 released — please redownload the GGUFs
-Hotfix for the chat template. If you downloaded this repo before v3, please redownload your GGUF.
-Fixes in v3:
-- embedded chat template updated for preserved reasoning and adaptive thinking;
-- fixes looping during long generation traces;
-- fixes agentic use in harnesses like OpenCode, Abacus, Hermes, and Claude Code;
 </td>
 </tr>
 </table>
 # Qwythos-9B-Claude-Mythos-5-1M-GGUF
 **Developed by [Empero](https://empero.org)**

 - agentic
 ---
 <table>
 <tr>
 <td>
+## 🚨 v2 released — please download the new model!
+We have release a version 2 of Qwythos here: **[empero-ai/Qwythos-9B-v2](https://huggingface.co/empero-ai/Qwythos-9B-v2)** or **[empero-ai/Qwythos-9B-v2-GGUF](https://huggingface.co/empero-ai/Qwythos-9B-v2-GGUF)**
+Please download the newest version for the best experience! If you downloaded Qwythos previously consider to download v2 for a rounder experience.
+Fixes include:
+- 🔁 Looping behavior eliminated — repetition/degeneration under greedy or low-temperature decoding dropped from 6.7% → 0%. You can serve it without leaning on repetition_penalty as a band-aid.
+- 🧠 Reasoning fully preserved — MMLU, GSM8K, GPQA, ARC and HumanEval are all held at (or above) the v1 level. This is a hygiene upgrade, not a capability regression.
+- 🧩 MTP head restored — the native multi-token-prediction module (dropped in the previous export) is back, so config and weights agree and speculative-decoding setups work.
+- 🪪 Cleaner identity — the model no longer prefaces unrelated answers with its identity; it introduces itself only when you actually ask.
+- 🔓 Still intentionally uncensored for research, cybersecurity, red-teaming, biology, chemistry, pharmacology and clinical work.
+- 📜 Still 1M-token context (YaRN) and the native multimodal-capable Qwen3.5 stack.
 </td>
 </tr>
 </table>
+<p align="center">
+  <img src="https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M/resolve/main/assets/qwythos.png" alt="Qwythos-9B" width="640"/>
+</p>
 # Qwythos-9B-Claude-Mythos-5-1M-GGUF
 **Developed by [Empero](https://empero.org)**