Instructions to use MoonieJeon/COSMOS-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Cosmos
How to use MoonieJeon/COSMOS-3B with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- llama-cpp-python
How to use MoonieJeon/COSMOS-3B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MoonieJeon/COSMOS-3B", filename="cosmos-3b.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MoonieJeon/COSMOS-3B 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 MoonieJeon/COSMOS-3B # Run inference directly in the terminal: llama cli -hf MoonieJeon/COSMOS-3B
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MoonieJeon/COSMOS-3B # Run inference directly in the terminal: llama cli -hf MoonieJeon/COSMOS-3B
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 MoonieJeon/COSMOS-3B # Run inference directly in the terminal: ./llama-cli -hf MoonieJeon/COSMOS-3B
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 MoonieJeon/COSMOS-3B # Run inference directly in the terminal: ./build/bin/llama-cli -hf MoonieJeon/COSMOS-3B
Use Docker
docker model run hf.co/MoonieJeon/COSMOS-3B
- LM Studio
- Jan
- Ollama
How to use MoonieJeon/COSMOS-3B with Ollama:
ollama run hf.co/MoonieJeon/COSMOS-3B
- Unsloth Studio
How to use MoonieJeon/COSMOS-3B 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 MoonieJeon/COSMOS-3B 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 MoonieJeon/COSMOS-3B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MoonieJeon/COSMOS-3B to start chatting
- Atomic Chat new
- Docker Model Runner
How to use MoonieJeon/COSMOS-3B with Docker Model Runner:
docker model run hf.co/MoonieJeon/COSMOS-3B
- Lemonade
How to use MoonieJeon/COSMOS-3B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MoonieJeon/COSMOS-3B
Run and chat with the model
lemonade run user.COSMOS-3B-{{QUANT_TAG}}List all available models
lemonade list
Update README.md
Browse files
README.md
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license: mit
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base_model: microsoft/Phi-3-mini-4k-instruct
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tags:
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# COSMOS-3B
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2. **Privacy:** On-device processing ensures that user data never leaves the local environment.
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3. **Interoperability:** Standardized GGUF format for cross-platform compatibility.
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## License
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This model is distributed under the **MIT** license. This ensures maximum flexibility and transparency for your projects.
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license: mit
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base_model: microsoft/Phi-3-mini-4k-instruct
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tags:
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language:
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---
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# COSMOS-3B
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2. **Privacy:** On-device processing ensures that user data never leaves the local environment.
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3. **Interoperability:** Standardized GGUF format for cross-platform compatibility.
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Compatibility
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COSMOS-3B is provided in GGUF format.
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It is compatible with all standard GGUF-compliant inference engines, including (but not limited to) LLamaSharp (C#), llama.cpp (C++), and various PHP-based LLM frameworks.
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## License
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This model is distributed under the **MIT** license. This ensures maximum flexibility and transparency for your projects.
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