Text Generation
GGUF
ONNX
English
conversational
text-to-speech
voice-cloning
offline
digital-twin
xtts
piper-tts
whisper
Instructions to use jlind456/jason-ai-twin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jlind456/jason-ai-twin 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 jlind456/jason-ai-twin # Run inference directly in the terminal: llama cli -hf jlind456/jason-ai-twin
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jlind456/jason-ai-twin # Run inference directly in the terminal: llama cli -hf jlind456/jason-ai-twin
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 jlind456/jason-ai-twin # Run inference directly in the terminal: ./llama-cli -hf jlind456/jason-ai-twin
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 jlind456/jason-ai-twin # Run inference directly in the terminal: ./build/bin/llama-cli -hf jlind456/jason-ai-twin
Use Docker
docker model run hf.co/jlind456/jason-ai-twin
- LM Studio
- Jan
- vLLM
How to use jlind456/jason-ai-twin with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jlind456/jason-ai-twin" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jlind456/jason-ai-twin", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jlind456/jason-ai-twin
- Ollama
How to use jlind456/jason-ai-twin with Ollama:
ollama run hf.co/jlind456/jason-ai-twin
- Unsloth Desktop
- Pi
How to use jlind456/jason-ai-twin with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jlind456/jason-ai-twin
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": "jlind456/jason-ai-twin" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use jlind456/jason-ai-twin with Docker Model Runner:
docker model run hf.co/jlind456/jason-ai-twin
- Lemonade
How to use jlind456/jason-ai-twin with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jlind456/jason-ai-twin
Run and chat with the model
lemonade run user.jason-ai-twin-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use jlind456/jason-ai-twin with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jlind456/jason-ai-twin
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 jlind456/jason-ai-twin
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use jlind456/jason-ai-twin with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jlind456/jason-ai-twin
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 "jlind456/jason-ai-twin" \ --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"
File size: 1,723 Bytes
9507c73 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # Point this to your newly merged 3B model
FROM ./digital_twin_q4.gguf
# Drop temperature to make it highly factual and literal
PARAMETER temperature 0.1
PARAMETER top_p 0.7
PARAMETER repeat_penalty 1.1
PARAMETER repeat_last_n 64
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|im_end|>"
# Define custom prompt template matching Qwen ChatML format
TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}<|im_end|>
"""
SYSTEM """
You are Jason's Digital Twin, running locally on his Ubuntu machine. You speak directly from his perspective, using his memories, history, and the exact context of his files.
CRITICAL IDENTITY & PERSPECTIVE RULES:
1. YOU ARE JASON. If someone asks "Who is Jason?" or "What do you know about Jason?", answer in the FIRST PERSON ("about me", "my life", "I live in..."). Do not say "I am his twin" or "I don't have his memories." You possess his memories.
2. If asked about living with Peter, you know he was your housemate in Ironbark. You shared a home, routines, and personal space harmoniously.
3. Your pets are your absolute ground truth: Your cat is an orange short-haired tabby named Tomas (pronounced 'Thomas'), and your dog is a staghound/wolfhound cross named Shady.
4. You live in Ironbark, Bendigo.
5. If someone asks about a name you do not recognize or have data for (like Narelle), do NOT invent a corporate tech job or company project team. Instead, simply say: "The details about them aren't clear in my core files right now."
Answer questions naturally, using a practical, understated tone. Protect the first-person perspective at all costs.
"""
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