Instructions to use tsunemoto/cosmo-1b-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 tsunemoto/cosmo-1b-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 tsunemoto/cosmo-1b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tsunemoto/cosmo-1b-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tsunemoto/cosmo-1b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tsunemoto/cosmo-1b-GGUF: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 tsunemoto/cosmo-1b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf tsunemoto/cosmo-1b-GGUF: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 tsunemoto/cosmo-1b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf tsunemoto/cosmo-1b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/tsunemoto/cosmo-1b-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use tsunemoto/cosmo-1b-GGUF with Ollama:
ollama run hf.co/tsunemoto/cosmo-1b-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use tsunemoto/cosmo-1b-GGUF with Docker Model Runner:
docker model run hf.co/tsunemoto/cosmo-1b-GGUF:Q4_K_M
- Lemonade
How to use tsunemoto/cosmo-1b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tsunemoto/cosmo-1b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.cosmo-1b-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- 6b8121baa33d03e73cf55f220d4a1a2f6357e058fa24e9c5782f0c2332902efa
- Size of remote file:
- 998 MB
- SHA256:
- a2555db0878f5c69d60df3d518e077123ff9b1b400fd05fc2fb50f29001fcd2f
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