Text Generation
GGUF
English
Japanese
llama.cpp
code-generation
javascript
typescript
react
nodejs
slm
conversational
Instructions to use ai-lqm/ai-localqmod-js-slm 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 ai-lqm/ai-localqmod-js-slm 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 ai-lqm/ai-localqmod-js-slm:Q4_K_M # Run inference directly in the terminal: llama cli -hf ai-lqm/ai-localqmod-js-slm:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ai-lqm/ai-localqmod-js-slm:Q4_K_M # Run inference directly in the terminal: llama cli -hf ai-lqm/ai-localqmod-js-slm: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 ai-lqm/ai-localqmod-js-slm:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf ai-lqm/ai-localqmod-js-slm: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 ai-lqm/ai-localqmod-js-slm:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf ai-lqm/ai-localqmod-js-slm:Q4_K_M
Use Docker
docker model run hf.co/ai-lqm/ai-localqmod-js-slm:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use ai-lqm/ai-localqmod-js-slm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ai-lqm/ai-localqmod-js-slm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ai-lqm/ai-localqmod-js-slm", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ai-lqm/ai-localqmod-js-slm:Q4_K_M
- Ollama
How to use ai-lqm/ai-localqmod-js-slm with Ollama:
ollama run hf.co/ai-lqm/ai-localqmod-js-slm:Q4_K_M
- Unsloth Studio
How to use ai-lqm/ai-localqmod-js-slm 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 ai-lqm/ai-localqmod-js-slm 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 ai-lqm/ai-localqmod-js-slm to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ai-lqm/ai-localqmod-js-slm to start chatting
- Atomic Chat new
- Docker Model Runner
How to use ai-lqm/ai-localqmod-js-slm with Docker Model Runner:
docker model run hf.co/ai-lqm/ai-localqmod-js-slm:Q4_K_M
- Lemonade
How to use ai-lqm/ai-localqmod-js-slm with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ai-lqm/ai-localqmod-js-slm:Q4_K_M
Run and chat with the model
lemonade run user.ai-localqmod-js-slm-Q4_K_M
List all available models
lemonade list
- Xet hash:
- 58fbe2e05fde28e47261a09af46c7bf2f6dc90d2deee0a670437d587f8bcf71d
- Size of remote file:
- 18.4 MB
- SHA256:
- 9b2b4038267307f47892a982bded63e35f6ca5a237524a4de1f5721496f1cc52
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