Medical Reasoning models
Collection
Medical reasoning models for medical purposes • 7 items • Updated • 3
How to use EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0 with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16 # Run inference directly in the terminal: llama cli -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16 # Run inference directly in the terminal: llama cli -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
# 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 EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16 # Run inference directly in the terminal: ./llama-cli -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
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 EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
docker model run hf.co/EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
How to use EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0 with Ollama:
ollama run hf.co/EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
How to use EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0 with Docker Model Runner:
docker model run hf.co/EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
How to use EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0 with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0:BF16
lemonade run user.Reasoning-Medical0.1-E4B-sft-Q8_0-BF16
lemonade list
This model was finetuned and converted to GGUF format using Unsloth.
Example usage:
llama-cli -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0 --jinjallama-mtmd-cli -hf EpistemeAI/Reasoning-Medical0.1-E4B-sft-Q8_0 --jinjagemma-4-E4B-it.Q8_0.ggufgemma-4-E4B-it.BF16-mmproj.ggufImportant: Ollama currently does not support separate mmproj files for vision models.
To create an Ollama model from this vision model:
Modelfile in the same directory as the finetuned bf16 merged modelollama create model_name -f ./Modelfile
(Replace model_name with your desired name)This will create a unified bf16 model that Ollama can use.
This was trained 2x faster with Unsloth

8-bit
Base model
google/gemma-4-E4B