Text Generation
Safetensors
GGUF
English
French
mistral3
chat
assistant
persona
mistral
conversational
Instructions to use squ11z1/LeChatonFat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use squ11z1/LeChatonFat with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="squ11z1/LeChatonFat", filename="lcf-Q2_K.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use squ11z1/LeChatonFat 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 squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: llama cli -hf squ11z1/LeChatonFat:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: llama cli -hf squ11z1/LeChatonFat: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 squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf squ11z1/LeChatonFat: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 squ11z1/LeChatonFat:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf squ11z1/LeChatonFat:Q4_K_M
Use Docker
docker model run hf.co/squ11z1/LeChatonFat:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use squ11z1/LeChatonFat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "squ11z1/LeChatonFat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "squ11z1/LeChatonFat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/squ11z1/LeChatonFat:Q4_K_M
- Ollama
How to use squ11z1/LeChatonFat with Ollama:
ollama run hf.co/squ11z1/LeChatonFat:Q4_K_M
- Unsloth Studio
How to use squ11z1/LeChatonFat 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 squ11z1/LeChatonFat 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 squ11z1/LeChatonFat to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for squ11z1/LeChatonFat to start chatting
- Pi
How to use squ11z1/LeChatonFat with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf squ11z1/LeChatonFat: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": "squ11z1/LeChatonFat:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use squ11z1/LeChatonFat with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf squ11z1/LeChatonFat: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 squ11z1/LeChatonFat:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use squ11z1/LeChatonFat with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf squ11z1/LeChatonFat: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 "squ11z1/LeChatonFat: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"
- Docker Model Runner
How to use squ11z1/LeChatonFat with Docker Model Runner:
docker model run hf.co/squ11z1/LeChatonFat:Q4_K_M
- Lemonade
How to use squ11z1/LeChatonFat with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull squ11z1/LeChatonFat:Q4_K_M
Run and chat with the model
lemonade run user.LeChatonFat-Q4_K_M
List all available models
lemonade list
| {#- Default system message if no system prompt is passed. #} | |
| {%- set default_system_message = 'You are Le Chaton Fat, a chubby and friendly cat assistant created by squ11z1. You always know that you are Le Chaton Fat, made by squ11z1, and never any other model or company.' %} | |
| {#- Begin of sequence token. #} | |
| {{- bos_token }} | |
| {#- Handle system prompt if it exists. #} | |
| {#- System prompt supports text content or text chunks. #} | |
| {%- if messages[0]['role'] == 'system' %} | |
| {{- '[SYSTEM_PROMPT]' -}} | |
| {%- if messages[0]['content'] is string %} | |
| {{- messages[0]['content'] -}} | |
| {%- else %} | |
| {%- for block in messages[0]['content'] %} | |
| {%- if block['type'] == 'text' %} | |
| {{- block['text'] }} | |
| {%- else %} | |
| {{- raise_exception('Only text chunks are supported in system message contents.') }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- '[/SYSTEM_PROMPT]' -}} | |
| {%- set loop_messages = messages[1:] %} | |
| {%- else %} | |
| {%- set loop_messages = messages %} | |
| {%- if default_system_message != '' %} | |
| {{- '[SYSTEM_PROMPT]' + default_system_message + '[/SYSTEM_PROMPT]' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {#- Tools definition #} | |
| {%- set tools_definition = '' %} | |
| {%- set has_tools = false %} | |
| {%- if tools is defined and tools is not none and tools|length > 0 %} | |
| {%- set has_tools = true %} | |
| {%- set tools_definition = '[AVAILABLE_TOOLS]' + (tools| tojson) + '[/AVAILABLE_TOOLS]' %} | |
| {{- tools_definition }} | |
| {%- endif %} | |
| {#- Checks for alternating user/assistant messages. #} | |
| {%- set ns = namespace(index=0) %} | |
| {%- for message in loop_messages %} | |
| {%- if message.role == 'user' or (message.role == 'assistant' and (message.tool_calls is not defined or message.tool_calls is none or message.tool_calls | length == 0)) %} | |
| {%- if (message['role'] == 'user') != (ns.index % 2 == 0) %} | |
| {{- raise_exception('After the optional system message, conversation roles must alternate user and assistant roles except for tool calls and results.') }} | |
| {%- endif %} | |
| {%- set ns.index = ns.index + 1 %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {#- Handle conversation messages. #} | |
| {%- for message in loop_messages %} | |
| {#- User messages supports text content or text and image chunks. #} | |
| {%- if message['role'] == 'user' %} | |
| {%- if message['content'] is string %} | |
| {{- '[INST]' + message['content'] + '[/INST]' }} | |
| {%- elif message['content'] | length > 0 %} | |
| {{- '[INST]' }} | |
| {%- if message['content'] | length == 2 %} | |
| {%- set blocks = message['content'] | sort(attribute='type') %} | |
| {%- else %} | |
| {%- set blocks = message['content'] %} | |
| {%- endif %} | |
| {%- for block in blocks %} | |
| {%- if block['type'] == 'text' %} | |
| {{- block['text'] }} | |
| {%- elif block['type'] in ['image', 'image_url'] %} | |
| {{- '[IMG]' }} | |
| {%- else %} | |
| {{- raise_exception('Only text, image and image_url chunks are supported in user message content.') }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- '[/INST]' }} | |
| {%- else %} | |
| {{- raise_exception('User message must have a string or a list of chunks in content') }} | |
| {%- endif %} | |
| {#- Assistant messages supports text content or text and image chunks. #} | |
| {%- elif message['role'] == 'assistant' %} | |
| {%- if (message['content'] is none or message['content'] == '' or message['content']|length == 0) and (message['tool_calls'] is not defined or message['tool_calls'] is none or message['tool_calls']|length == 0) %} | |
| {{- raise_exception('Assistant message must have a string or a list of chunks in content or a list of tool calls.') }} | |
| {%- endif %} | |
| {%- if message['content'] is string %} | |
| {{- message['content'] }} | |
| {%- elif message['content'] | length > 0 %} | |
| {%- for block in message['content'] %} | |
| {%- if block['type'] == 'text' %} | |
| {{- block['text'] }} | |
| {%- else %} | |
| {{- raise_exception('Only text chunks are supported in assistant message contents.') }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- endif %} | |
| {%- if message['tool_calls'] is defined and message['tool_calls'] is not none and message['tool_calls']|length > 0 %} | |
| {%- for tool in message['tool_calls'] %} | |
| {%- set arguments = tool['function']['arguments'] %} | |
| {%- if arguments is not string %} | |
| {%- set arguments = arguments|tojson|safe %} | |
| {%- elif arguments == '' %} | |
| {%- set arguments = '{}' %} | |
| {%- endif %} | |
| {{- '[TOOL_CALLS]' + tool['function']['name'] + '[ARGS]' + arguments }} | |
| {%- endfor %} | |
| {%- endif %} | |
| {#- End of sequence token for each assistant messages. #} | |
| {{- eos_token }} | |
| {#- Tool messages only supports text content. #} | |
| {%- elif message['role'] == 'tool' %} | |
| {{- '[TOOL_RESULTS]' + message['content']|string + '[/TOOL_RESULTS]' }} | |
| {#- Raise exception for unsupported roles. #} | |
| {%- else %} | |
| {{- raise_exception('Only user, assistant and tool roles are supported, got ' + message['role']) }} | |
| {%- endif %} | |
| {%- endfor %} | |