Instructions to use jerinaj/lfm-tool 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 jerinaj/lfm-tool 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 jerinaj/lfm-tool:Q4_K_M # Run inference directly in the terminal: llama cli -hf jerinaj/lfm-tool:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jerinaj/lfm-tool:Q4_K_M # Run inference directly in the terminal: llama cli -hf jerinaj/lfm-tool: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 jerinaj/lfm-tool:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf jerinaj/lfm-tool: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 jerinaj/lfm-tool:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf jerinaj/lfm-tool:Q4_K_M
Use Docker
docker model run hf.co/jerinaj/lfm-tool:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use jerinaj/lfm-tool with Ollama:
ollama run hf.co/jerinaj/lfm-tool:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use jerinaj/lfm-tool with Docker Model Runner:
docker model run hf.co/jerinaj/lfm-tool:Q4_K_M
- Lemonade
How to use jerinaj/lfm-tool with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jerinaj/lfm-tool:Q4_K_M
Run and chat with the model
lemonade run user.lfm-tool-Q4_K_M
List all available models
lemonade list
- Atomic Chat
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Download README.md from jerinaj/lfm-tool: direct link, hf CLI and curl.
- Browser
- Download file 702 Bytes
-
https://huggingface.co/jerinaj/lfm-tool/resolve/main/README.md
- Command line
-
hf download hf://jerinaj/lfm-tool/README.md
-
curl -L -o README.md https://huggingface.co/jerinaj/lfm-tool/resolve/main/README.md
702 Bytes
| tags: | |
| - gguf | |
| - llama.cpp | |
| - unsloth | |
| # lfm-tool : GGUF | |
| This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth). | |
| **Example usage**: | |
| - For text only LLMs: `llama-cli -hf jerinaj/lfm-tool --jinja` | |
| - For multimodal models: `llama-mtmd-cli -hf jerinaj/lfm-tool --jinja` | |
| ## Available Model files: | |
| - `LFM2-350M.Q4_K_M.gguf` | |
| ## Note | |
| The model's BOS token behavior was adjusted for GGUF compatibility. | |
| This was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) | |
| [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) | |