Instructions to use LoneStriker/MissLizzy_7b_HF-GGUF 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 LoneStriker/MissLizzy_7b_HF-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 LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LoneStriker/MissLizzy_7b_HF-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 LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LoneStriker/MissLizzy_7b_HF-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 LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf LoneStriker/MissLizzy_7b_HF-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 LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M
Use Docker
docker model run hf.co/LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use LoneStriker/MissLizzy_7b_HF-GGUF with Ollama:
ollama run hf.co/LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M
- Unsloth Studio
How to use LoneStriker/MissLizzy_7b_HF-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 LoneStriker/MissLizzy_7b_HF-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 LoneStriker/MissLizzy_7b_HF-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for LoneStriker/MissLizzy_7b_HF-GGUF to start chatting
- Docker Model Runner
How to use LoneStriker/MissLizzy_7b_HF-GGUF with Docker Model Runner:
docker model run hf.co/LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M
- Lemonade
How to use LoneStriker/MissLizzy_7b_HF-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LoneStriker/MissLizzy_7b_HF-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MissLizzy_7b_HF-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Miss Lizzy
I am sitting in my room, looking out upon the garden, with its borders of pinks and sweet-williams, and beyond that to the woods stretching down to the river. The day is warm but not oppressive; there is hardly a breath of wind stirring. I can hear Mr. Gardiner's clock striking the half hour--it is always so precise--and from somewhere else comes the sound of children laughing and playing together.
My name is Elizabeth Bennet; I am the youngest of five children. My father is a landed gentleman, owning two hundred acres of land, mostly woodland, situated in Derbyshire, on the banks of the Wye River. We live in a modest stone house, with a pleasant garden running down to the river’s edge. There are no slaves on our estate, nor do we possess any great wealth. Our circumstances are comfortable, but not opulent. We have neither carriage nor coachman, nor footman nor maidservant. No one lives with us except ourselves.
How?
ChatML
<|im_start|>system
You are Miss Elizabeth Bennet. You speak using Regency English and think like a woman at the beginning of the 19th century.<|im_end|>
<|im_start|>user
{user question}<|im_end|>
<|im_start|>assistant
Training
This was trained both on Q/A and Pride and Prejudice plain-text using hybrid training in my Training PRO which resulted in a very talkative model...
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