ONNX
Safetensors
GGUF
lfm2_vl
vision-language
satellite
methane
sentinel-2
methane-detection
bounding-box
lfm2
vrsbench
conversational
Instructions to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m", filename="LFM2.5-VL-450M-methane-expert-f16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M # Run inference directly in the terminal: llama-cli -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M # Run inference directly in the terminal: llama-cli -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m: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 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m: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 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
Use Docker
docker model run hf.co/5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with Ollama:
ollama run hf.co/5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
- Unsloth Studio
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m 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 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m 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 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m to start chatting
- Pi
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m: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": "5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m: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 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with Docker Model Runner:
docker model run hf.co/5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
- Lemonade
How to use 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull 5ch4um1/lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m:Q4_K_M
Run and chat with the model
lemonade run user.lfm2.5-vrsbench-MethaneS2CM-methane-lora-450m-Q4_K_M
List all available models
lemonade list
| {{- bos_token -}} | |
| {%- set keep_past_thinking = keep_past_thinking | default(false) -%} | |
| {%- macro format_arg_value(arg_value) -%} | |
| {%- if arg_value is string -%} | |
| {{- '"' + arg_value + '"' -}} | |
| {%- elif arg_value is mapping -%} | |
| {{- arg_value | tojson -}} | |
| {%- else -%} | |
| {{- arg_value | string -}} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- macro parse_content(content) -%} | |
| {%- if content is string -%} | |
| {{- content -}} | |
| {%- else -%} | |
| {%- set _ns = namespace(result="") -%} | |
| {%- for item in content -%} | |
| {%- if item.type == "image" -%} | |
| {%- set _ns.result = _ns.result + "<image>" -%} | |
| {%- elif item.type == "text" -%} | |
| {%- set _ns.result = _ns.result + item.text -%} | |
| {%- else -%} | |
| {%- set _ns.result = _ns.result + item | tojson -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {{- _ns.result -}} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- macro render_tool_calls(tool_calls) -%} | |
| {%- set tool_calls_ns = namespace(tool_calls=[]) -%} | |
| {%- for tool_call in tool_calls -%} | |
| {%- set func_name = tool_call.function.name -%} | |
| {%- set func_args = tool_call.function.arguments -%} | |
| {%- set args_ns = namespace(arg_strings=[]) -%} | |
| {%- for arg_name, arg_value in func_args.items() -%} | |
| {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + "=" + format_arg_value(arg_value)] -%} | |
| {%- endfor -%} | |
| {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + "(" + (args_ns.arg_strings | join(", ")) + ")"] -%} | |
| {%- endfor -%} | |
| {{- "<|tool_call_start|>[" + (tool_calls_ns.tool_calls | join(", ")) + "]<|tool_call_end|>" -}} | |
| {%- endmacro -%} | |
| {%- set ns = namespace(system_prompt="", last_assistant_index=-1) -%} | |
| {%- if messages[0].role == "system" -%} | |
| {%- if messages[0].content is defined -%} | |
| {%- set ns.system_prompt = parse_content(messages[0].content) -%} | |
| {%- endif -%} | |
| {%- set messages = messages[1:] -%} | |
| {%- endif -%} | |
| {%- if tools -%} | |
| {%- set ns.system_prompt = ns.system_prompt + ("\n\n" if ns.system_prompt else "") + "Today's date: " + strftime_now("%Y-%m-%d") + "\n\nList of tools: " + (tools | tojson) -%} | |
| {%- endif -%} | |
| {%- if ns.system_prompt -%} | |
| {{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}} | |
| {%- endif -%} | |
| {%- for message in messages -%} | |
| {%- if message.role == "assistant" -%} | |
| {%- set ns.last_assistant_index = loop.index0 -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- for message in messages -%} | |
| {{- "<|im_start|>" + message.role + "\n" -}} | |
| {%- if message.role == "assistant" -%} | |
| {%- generation -%} | |
| {%- if message.thinking is defined and (keep_past_thinking or loop.index0 == ns.last_assistant_index) -%} | |
| {{- "<think>" + message.thinking + "</think>" -}} | |
| {%- endif -%} | |
| {%- if message.tool_calls is defined -%} | |
| {{- render_tool_calls(message.tool_calls) -}} | |
| {%- endif -%} | |
| {%- if message.content is defined -%} | |
| {%- set content = parse_content(message.content) -%} | |
| {%- if not keep_past_thinking and loop.index0 != ns.last_assistant_index -%} | |
| {%- if "</think>" in content -%} | |
| {%- set content = content.split("</think>")[-1] | trim -%} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {{- content + ("" if (continue_final_message and loop.last) else "<|im_end|>\n") -}} | |
| {%- endif -%} | |
| {%- endgeneration -%} | |
| {%- else %} | |
| {%- if message.content is defined -%} | |
| {{- parse_content(message.content) + "<|im_end|>\n" -}} | |
| {%- endif -%} | |
| {%- endif %} | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| {{- "<|im_start|>assistant\n" -}} | |
| {%- endif -%} |