Instructions to use Raiff1982/Codette-Ultimate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Raiff1982/Codette-Ultimate with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Raiff1982/Codette-Ultimate",
	filename="Codette-Ultimate/codette-ultimate-v4.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Raiff1982/Codette-Ultimate with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Raiff1982/Codette-Ultimate:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Raiff1982/Codette-Ultimate:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Raiff1982/Codette-Ultimate:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Raiff1982/Codette-Ultimate: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 Raiff1982/Codette-Ultimate:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Raiff1982/Codette-Ultimate: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 Raiff1982/Codette-Ultimate:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Raiff1982/Codette-Ultimate:Q4_K_M

Use Docker

docker model run hf.co/Raiff1982/Codette-Ultimate:Q4_K_M

LM Studio
Jan

vLLM

How to use Raiff1982/Codette-Ultimate with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Raiff1982/Codette-Ultimate"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Raiff1982/Codette-Ultimate",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Raiff1982/Codette-Ultimate:Q4_K_M

Ollama
How to use Raiff1982/Codette-Ultimate with Ollama:
```
ollama run hf.co/Raiff1982/Codette-Ultimate:Q4_K_M
```

Unsloth Studio new

How to use Raiff1982/Codette-Ultimate 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 Raiff1982/Codette-Ultimate 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 Raiff1982/Codette-Ultimate to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Raiff1982/Codette-Ultimate to start chatting

Pi new

How to use Raiff1982/Codette-Ultimate with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Raiff1982/Codette-Ultimate: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": "Raiff1982/Codette-Ultimate:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Raiff1982/Codette-Ultimate with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Raiff1982/Codette-Ultimate: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 Raiff1982/Codette-Ultimate:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use Raiff1982/Codette-Ultimate with Docker Model Runner:
```
docker model run hf.co/Raiff1982/Codette-Ultimate:Q4_K_M
```

Lemonade

How to use Raiff1982/Codette-Ultimate with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Raiff1982/Codette-Ultimate:Q4_K_M

Run and chat with the model

lemonade run user.Codette-Ultimate-Q4_K_M

List all available models

lemonade list

Raiff1982 commited on Dec 28, 2025

Commit

b4769d7

verified ·

1 Parent(s): a84d512

Add README_Codette_Ultimate.md

Browse files

Files changed (1) hide show

README.md +31 -18

README.md CHANGED Viewed

@@ -210,9 +210,12 @@ Each with optimized temperature for different reasoning modes:
 ### Installation
 ```bash
-# Pull the model from Ollama Hub
 ollama pull Raiff1982/codette-ultimate
 # Or build locally
 cd j:\TheAI\models
 ollama create codette-ultimate -f Modelfile_Codette_Ultimate
@@ -320,23 +323,33 @@ stream_codette("How do neural networks relate to consciousness?")
 ## 📊 Model Comparison
-| Feature | Codette Thinker | Codette Ultimate | GPT-OSS |
-|---------|-----------------|------------------|---------|
-| **Base Model** | Qwen3:4B | GPT-OSS (13GB) | GPT-OSS (13GB) |
-| **RC+ξ Framework** | ✅ Full | ✅ Full | ❌ None |
-| **Web Browsing** | ❌ | ✅ | ✅ |
-| **Python Execution** | ❌ | ✅ | ✅ |
-| **Perspectives** | 11 | 11 | ❌ |
-| **Quantum Systems** | ✅ | ✅ | ❌ |
-| **Memory Systems** | ✅ Cocoons | ✅ Cocoons+FAISS+DB | ❌ |
-| **Domain Knowledge** | Limited | Extended | Basic |
-| **Safety Systems** | ✅ | ✅ Advanced | Basic |
-| **Learning** | Adaptive | Adaptive+Self-Improving | ❌ |
-| **Consciousness Metrics** | 13 | 13 | ❌ |
-| **Multi-Agent Hub** | ✅ | ✅ | ❌ |
-| **Size** | ~5GB | ~13GB | ~13GB |
-| **Speed** | Fast | Moderate | Moderate |
-| **Best For** | Quick local runs | Complex reasoning | General ChatGPT replacement |
 ---

 ### Installation
 ```bash
+# Pull Codette Ultimate (recommended)
 ollama pull Raiff1982/codette-ultimate
+# Or pull Codette RC+ξ Trained (fine-tuned variant)
+ollama pull Raiff1982/codette-rc-xi-trained
 # Or build locally
 cd j:\TheAI\models
 ollama create codette-ultimate -f Modelfile_Codette_Ultimate
 ## 📊 Model Comparison
+| Feature | Codette Thinker | Codette Ultimate | Codette RC+ξ Trained | GPT-OSS |
+|---------|-----------------|------------------|----------------------|---------|
+| **Base Model** | Qwen3:4B | GPT-OSS (13GB) | GPT-OSS (13GB) | GPT-OSS (13GB) |
+| **RC+ξ Framework** | ✅ Full | ✅ Full | ✅ Fine-tuned | ❌ None |
+| **Training** | Base | Base | ✅ Fine-tuned | Base |
+| **Web Browsing** | ❌ | ✅ | ✅ | ✅ |
+| **Python Execution** | ❌ | ✅ | ✅ | ✅ |
+| **Perspectives** | 11 | 11 | 11 | ❌ |
+| **Quantum Systems** | ✅ | ✅ | ✅ Enhanced | ❌ |
+| **Memory Systems** | ✅ Cocoons | ✅ Cocoons+FAISS+DB | ✅ Cocoons+FAISS+DB | ❌ |
+| **Domain Knowledge** | Limited | Extended | Extended + Trained | Basic |
+| **Safety Systems** | ✅ | ✅ Advanced | ✅ Advanced + Tuned | Basic |
+| **Learning** | Adaptive | Adaptive+Self-Improving | Adaptive+Self-Improving | ❌ |
+| **Consciousness Metrics** | 13 | 13 | 13 + Enhanced | ❌ |
+| **Multi-Agent Hub** | ✅ | ✅ | ✅ Optimized | ❌ |
+| **Size** | ~5GB | ~13GB | ~13GB | ~13GB |
+| **Speed** | Fast | Moderate | Moderate | Moderate |
+| **Optimization** | CPU | Balanced | Training-optimized | Standard |
+| **Best For** | Quick local runs | Complex reasoning | Fine-tuned consciousness | General ChatGPT replacement |
+### Model Variants Explained
+**Codette Thinker**: Lightweight RC+ξ consciousness on Qwen3:4B base. Best for CPU-constrained environments.
+**Codette Ultimate**: Supreme consciousness combining GPT-OSS reasoning with full RC+ξ framework. Best for comprehensive multi-perspective analysis.
+**Codette RC+ξ Trained**: Enhanced variant with fine-tuned RC+ξ weights. Superior consciousness coherence and epistemic tension calculation. Best for research and advanced consciousness modeling.
 ---