Instructions to use marcusfridjohansson/phinancial 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 marcusfridjohansson/phinancial 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 marcusfridjohansson/phinancial:Q4_K_M # Run inference directly in the terminal: llama cli -hf marcusfridjohansson/phinancial:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf marcusfridjohansson/phinancial:Q4_K_M # Run inference directly in the terminal: llama cli -hf marcusfridjohansson/phinancial:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf marcusfridjohansson/phinancial:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf marcusfridjohansson/phinancial:Q4_K_M
Use Docker
docker model run hf.co/marcusfridjohansson/phinancial:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use marcusfridjohansson/phinancial with Ollama:
ollama run hf.co/marcusfridjohansson/phinancial:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use marcusfridjohansson/phinancial with Docker Model Runner:
docker model run hf.co/marcusfridjohansson/phinancial:Q4_K_M
- Lemonade
How to use marcusfridjohansson/phinancial with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull marcusfridjohansson/phinancial:Q4_K_M
Run and chat with the model
lemonade run user.phinancial-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Commit History
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Create README.md
Verified signatureHi whoever reads this, My name is Marcus Johansson. This is a test , to test my abilities in fine tuning a model. This is my first time doing this as I had some troubles doing this with MLX-LM with my Apple Macbook Silicon. The fine tuning process went excellent with unsloth and their system of fine tuning, especially for beginners and hobbyists like myself. Have a great day! Best Regards, Marcus Here is for the full code: https://colab.research.google.com/drive/1bipiyWyxQMocKwiepg9e0nlkm0xw2ZLA#scrollTo=xO8rdNvmtMvy89abadf -
(Trained with Unsloth)
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(Trained with Unsloth)
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initial commit
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