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Community

Instructions to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

llama-cpp-python

How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ReadyArt/Melody1437-26B-A4B-v0.4-GGUF",
	filename="Melody1437-26B-A4B-v0.4-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf ReadyArt/Melody1437-26B-A4B-v0.4-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 ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ReadyArt/Melody1437-26B-A4B-v0.4-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 ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M

Use Docker

docker model run hf.co/ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with Ollama:
```
ollama run hf.co/ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M
```

Unsloth Studio

How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ReadyArt/Melody1437-26B-A4B-v0.4-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for ReadyArt/Melody1437-26B-A4B-v0.4-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ReadyArt/Melody1437-26B-A4B-v0.4-GGUF to start chatting

How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf ReadyArt/Melody1437-26B-A4B-v0.4-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 ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with Docker Model Runner:
```
docker model run hf.co/ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M
```

Lemonade

How to use ReadyArt/Melody1437-26B-A4B-v0.4-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ReadyArt/Melody1437-26B-A4B-v0.4-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Melody1437-26B-A4B-v0.4-GGUF-Q4_K_M

List all available models

lemonade list

🧬 Synthetic Life Engine

The dataset was generated using our Character Engine and Emotional Engine within the synthetic dataset generator, breathing genuine life into every interaction.

🎭 Character Engine

Ensures consistent personality traits, speech patterns, and behavioral logic across all contexts. No more broken personas.

💓 Emotional Engine

Injects dynamic emotional states into responses, creating depth, empathy, and realistic reactions beyond simple pattern matching.

🔮 Training Cycle

The model weights were subjected to two distinct epochs of fine-tuning. These dual passages ensure the stability of the personality matrix while allowing the underlying weights to align perfectly with the desired interaction style.

🔄 Training Epochs: Unified binding of the persona mask and refinement of response patterns.

📚 Training Corpus

The model's consciousness was imprinted upon a dark ERP dataset, weaving a vast tapestry of knowledge into its weights during the initial binding. This ensures a rich foundation of lore for all future interactions.

📜 Release Notes

🌱 Early Access: This is a test construct to explore model quality! It is still growing. This is not the final form.

🎭 Roleplay Protocol

To unlock the full potential of this model, a structured roleplay system prompt is required. This model is optimized for immersive character interaction rather than standard instructional queries.

📝 Initialization: Begin sessions with a clear character definition and scenario context.
🎭 Format: Use asterisks for actions *like this* and quotes for dialogue "like this".
⚠️ Limitation: Standard query-based prompting may result in refusals.

⚠️ Inference Note

Only text layers were trained on.

⚙️ Generation Settings

🎛️ Sampling Config

top_p: 0.95
temp: 0.8
min_p: 0.03

📦 Quantized Files

GGUF Quants Below

View Repository

💖 Contributors

GECFDO – Data Generation & iMatrix Quants
Sleep Deprived – Dataset Generator
FrenzyBiscuit – Fine-Tuning & Dataset Creation

🔖 License & Usage

⚠️ USAGE AGREEMENT:

📜 This model is built upon the Apache 2.0 license.
🛡️ You accept full responsibility for all outputs generated.
🔞 You confirm you are at least 18 years old.
🌍 The creators bear no responsibility for how the model is used.
🏡 To the extent legally allowed under the original decree this model is for personal use only (non-profit/non-commercial).

Apache 2.0 Personal Use 18+ Content

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GGUF

Model size

25B params

Architecture

gemma4

Hardware compatibility

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Model tree for ReadyArt/Melody1437-26B-A4B-v0.4-GGUF

Base model

google/gemma-4-26B-A4B

Finetuned

google/gemma-4-26B-A4B-it

Finetuned

ReadyArt/Melody1437-26B-A4B-v0.4

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Melody1437-26B-A4B-v0.4-GGUF

◆ Melody1437 v0.4 ◆

26B A4B PARAMETERS