Instructions to use cortexso/olmo-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use cortexso/olmo-2 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="cortexso/olmo-2", filename="olmo-2-0325-32b-instruct-q2_k.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use cortexso/olmo-2 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf cortexso/olmo-2:Q4_K_M # Run inference directly in the terminal: llama-cli -hf cortexso/olmo-2:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf cortexso/olmo-2:Q4_K_M # Run inference directly in the terminal: llama-cli -hf cortexso/olmo-2: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 cortexso/olmo-2:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf cortexso/olmo-2: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 cortexso/olmo-2:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf cortexso/olmo-2:Q4_K_M
Use Docker
docker model run hf.co/cortexso/olmo-2:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use cortexso/olmo-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cortexso/olmo-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cortexso/olmo-2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/cortexso/olmo-2:Q4_K_M
- Ollama
How to use cortexso/olmo-2 with Ollama:
ollama run hf.co/cortexso/olmo-2:Q4_K_M
- Unsloth Studio new
How to use cortexso/olmo-2 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 cortexso/olmo-2 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 cortexso/olmo-2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cortexso/olmo-2 to start chatting
- Docker Model Runner
How to use cortexso/olmo-2 with Docker Model Runner:
docker model run hf.co/cortexso/olmo-2:Q4_K_M
- Lemonade
How to use cortexso/olmo-2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cortexso/olmo-2:Q4_K_M
Run and chat with the model
lemonade run user.olmo-2-Q4_K_M
List all available models
lemonade list
Update README.md
Browse files
README.md
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## Use it with Jan (UI)
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## Credits
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- **Author:** allenai
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- **Converter:** [Homebrew]
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- **Original License:** [Licence]
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- **Papers:** [Paper]
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| 1 | [Olmo-2-7b](https://huggingface.co/cortexso/olmo-2/tree/7b) | `cortex run olmo-2:7b` |
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| 2 | [Olmo-2-13b](https://huggingface.co/cortexso/olmo-2/tree/13b) | `cortex run olmo-2:13b` |
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## Use it with Jan (UI)
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## Credits
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- **Author:** allenai
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- **Converter:** [Homebrew](https://homebrew.ltd/)
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- **Original License:** [Licence](https://choosealicense.com/licenses/apache-2.0/)
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- **Papers:** [Paper](https://arxiv.org/abs/2501.00656)
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