Instructions to use lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
Use Docker
docker model run hf.co/lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use lmstudio-community/DeepSWE-Preview-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lmstudio-community/DeepSWE-Preview-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lmstudio-community/DeepSWE-Preview-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
- Ollama
How to use lmstudio-community/DeepSWE-Preview-GGUF with Ollama:
ollama run hf.co/lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
- Unsloth Studio
How to use lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for lmstudio-community/DeepSWE-Preview-GGUF to start chatting
- Pi
How to use lmstudio-community/DeepSWE-Preview-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lmstudio-community/DeepSWE-Preview-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": "lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use lmstudio-community/DeepSWE-Preview-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lmstudio-community/DeepSWE-Preview-GGUF: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 "lmstudio-community/DeepSWE-Preview-GGUF: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 lmstudio-community/DeepSWE-Preview-GGUF with Docker Model Runner:
docker model run hf.co/lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
- Lemonade
How to use lmstudio-community/DeepSWE-Preview-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.DeepSWE-Preview-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use lmstudio-community/DeepSWE-Preview-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf lmstudio-community/DeepSWE-Preview-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 lmstudio-community/DeepSWE-Preview-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
jinja template wrong on LM Studio
Hello,
The default jinja template is wrong and will not allow for any response on LM Studio. Is there a fix?
Thank you.
{%- if tools %}
{{- '<|im_start|>system\n' }}
{%- if messages[0].role == 'system' %}
{{- messages[0].content + '\n\n' }}
{%- endif %}
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{"name": , "arguments": }\n<|im_end|>\n" }}
{%- else %}
{%- if messages[0].role == 'system' %}
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
{%- for index in range(ns.last_query_index, -1, -1) %}
{%- set message = messages[index] %}
{%- if ns.multi_step_tool and message.role == "user" and not('' in message.content and '' in message.content) %}
{%- set ns.multi_step_tool = false %}
{%- set ns.last_query_index = index %}
{%- endif %}
{%- endfor %}
{%- for message in messages %}
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
{%- elif message.role == "assistant" %}
{%- set content = message.content %}
{%- set reasoning_content = '' %}
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
{%- set reasoning_content = message.reasoning_content %}
{%- else %}
{%- if '' in message.content %}
{%- set content = (message.content.split('')|last).lstrip('\n') %}
{%- set reasoning_content = (message.content.split('')|first).rstrip('\n') %}
{%- set reasoning_content = (reasoning_content.split('')|last).lstrip('\n') %}
{%- endif %}
{%- endif %}
{%- if loop.index0 > ns.last_query_index %}
{%- if loop.last or (not loop.last and reasoning_content) %}
{{- '<|im_start|>' + message.role + '\n\n' + reasoning_content.strip('\n') + '\n\n\n' + content.lstrip('\n') }}
{%- else %}
{{- '<|im_start|>' + message.role + '\n' + content }}
{%- endif %}
{%- else %}
{{- '<|im_start|>' + message.role + '\n' + content }}
{%- endif %}
{%- if message.tool_calls %}
{%- for tool_call in message.tool_calls %}
{%- if (loop.first and content) or (not loop.first) %}
{{- '\n' }}
{%- endif %}
{%- if tool_call.function %}
{%- set tool_call = tool_call.function %}
{%- endif %}
{{- '\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{%- if tool_call.arguments is string %}
{{- tool_call.arguments }}
{%- else %}
{{- tool_call.arguments | tojson }}
{%- endif %}
{{- '}\n' }}
{%- endfor %}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n\n' }}
{{- message.content }}
{{- '\n' }}
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
{{- '<|im_end|>\n' }}
{%- endif %}
{%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- if enable_thinking is defined and enable_thinking is false %}
{{- '\n\n\n\n' }}
{%- endif %}
{%- endif %}
This version seems borked. I'm downloading straight from @bartowski to see if that one works.
Edit: Nope, they all seem to have the same error.