Image-Text-to-Text
Transformers
Safetensors
GGUF
English
lfm2_vl
vision-language
earth-observation
remote-sensing
sentinel-2
vrsbench
tailings-dam
gistm
compliance
lora
lfm2-vl
liquid-ai
satdiff
conversational
Instructions to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1") model = AutoModelForMultimodalLM.from_pretrained("WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 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 WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0 # Run inference directly in the terminal: llama cli -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0 # Run inference directly in the terminal: llama cli -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
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 WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
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 WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
Use Docker
docker model run hf.co/WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
- LM Studio
- Jan
- vLLM
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
- SGLang
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Ollama
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with Ollama:
ollama run hf.co/WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
- Unsloth Desktop
- Pi
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
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": "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with Docker Model Runner:
docker model run hf.co/WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
- Lemonade
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
Run and chat with the model
lemonade run user.SatDiff-LFM2.5-VL-450M-stage1-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
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 WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0
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 "WobblyDopamine/SatDiff-LFM2.5-VL-450M-stage1:Q8_0" \ --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: 3,836 Bytes
c1dc2ee | 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | {{- 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 -%} |