How to use from
llama.cpp
# Gated model: Login with a HF token with gated access permission
hf auth login
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf whyhow-ai/PatientSeek:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf whyhow-ai/PatientSeek:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf whyhow-ai/PatientSeek:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf whyhow-ai/PatientSeek: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 whyhow-ai/PatientSeek:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf whyhow-ai/PatientSeek: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 whyhow-ai/PatientSeek:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf whyhow-ai/PatientSeek:Q4_K_M
Use Docker
docker model run hf.co/whyhow-ai/PatientSeek:Q4_K_M
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Model Card for Model ID

This model has been finetuned on patient records from over 10,000 patients, with full histories. It's been specifically tuned on summarisation, basic QA for extraction, and reasoned hypothesis for causation for medical-legal usecases.

Model Details

Model Description

Model Sources [optional]

Uses

Used for summarising one to many medical records for patients, for basic QA of medical records, and for hypothesis testing in the form of associative reasoning.

How to Get Started with the Model

The best instructions on how to run are here: https://unsloth.ai/blog/deepseek-r1

Model Card Contact

Email us at team@whyhow.ai.

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llama
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