Instructions to use NobodyWho/LFM2.5-1.2B-Instruct-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 NobodyWho/LFM2.5-1.2B-Instruct-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 NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16 # Run inference directly in the terminal: llama cli -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16 # Run inference directly in the terminal: llama cli -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
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 NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16 # Run inference directly in the terminal: ./llama-cli -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
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 NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
Use Docker
docker model run hf.co/NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
- Llama new
- LM Studio
- Jan
- Ollama
How to use NobodyWho/LFM2.5-1.2B-Instruct-GGUF with Ollama:
ollama run hf.co/NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
- Unsloth Desktop
- Pi
How to use NobodyWho/LFM2.5-1.2B-Instruct-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
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": "NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use NobodyWho/LFM2.5-1.2B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
- Lemonade
How to use NobodyWho/LFM2.5-1.2B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
Run and chat with the model
lemonade run user.LFM2.5-1.2B-Instruct-GGUF-F16
List all available models
lemonade list
- Hermes Agent
How to use NobodyWho/LFM2.5-1.2B-Instruct-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 NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
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 NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use NobodyWho/LFM2.5-1.2B-Instruct-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16
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 "NobodyWho/LFM2.5-1.2B-Instruct-GGUF:F16" \ --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"
Commit History
-
Strip penalty_last_n (non-vendor llama.cpp default); general.sampling.* now matches LiquidAI's leap config exactly (temp, min_p, repetition_penalty)
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Strip penalty_last_n (non-vendor llama.cpp default); general.sampling.* now matches LiquidAI's leap config exactly (temp, min_p, repetition_penalty)
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Remove penalty_last_n note (the key was stripped from the GGUFs instead)
Verified signature9439d0f -
Document penalty_last_n=64 provenance: NobodyWho-injected llama.cpp default (repetition-penalty window), not a vendor-specified value
Verified signaturee191145
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Sampling notes: re-verified tool-suite scores under corrected sampler (Q8_0 14/14, F16 14/14 sampling-free, Q4_0 12/14); F16 stays sampling-free
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Correct sampling notes to LEAP config values; flag tool scores predate the correction
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Fix vendor sampling to LiquidAI LEAP config: temp 0.3, min_p 0.15, repetition_penalty 1.05 (was temp 0.1 + stray top_k 50, no min_p)
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Fix vendor sampling to LiquidAI LEAP config: temp 0.3, min_p 0.15, repetition_penalty 1.05 (was temp 0.1 + stray top_k 50, no min_p)
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Model card: add capabilities, getting started, tool-calling example, model details
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Update file names after vendor-sampling rename
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Rename: mark vendor-sampling files explicitly
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Fix intro: repo holds multiple quants, not only Q8_0
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Update Q8_0 recipe in file table
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Add vendor sampling metadata to Q8_0 (verified 14/14 active and inert)
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Document file variants and scores
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Add Q4_0 with vendor sampling metadata
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Add F16 (template fix only)
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LFM2.5-1.2B-Instruct Q8_0 with tool_calls chat-template fix
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Add LICENSE
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Add README.md
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initial commit
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