Instructions to use samrawal/problem-list-generator-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use samrawal/problem-list-generator-Q8_0-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="samrawal/problem-list-generator-Q8_0-GGUF",
	filename="problem-list-generator-q8_0.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 samrawal/problem-list-generator-Q8_0-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf samrawal/problem-list-generator-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf samrawal/problem-list-generator-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama-cli -hf samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

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 samrawal/problem-list-generator-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

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 samrawal/problem-list-generator-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

LM Studio
Jan

vLLM

How to use samrawal/problem-list-generator-Q8_0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "samrawal/problem-list-generator-Q8_0-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "samrawal/problem-list-generator-Q8_0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

Ollama
How to use samrawal/problem-list-generator-Q8_0-GGUF with Ollama:
```
ollama run hf.co/samrawal/problem-list-generator-Q8_0-GGUF:Q8_0
```

Unsloth Studio new

How to use samrawal/problem-list-generator-Q8_0-GGUF 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 samrawal/problem-list-generator-Q8_0-GGUF 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 samrawal/problem-list-generator-Q8_0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for samrawal/problem-list-generator-Q8_0-GGUF to start chatting

Docker Model Runner
How to use samrawal/problem-list-generator-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/samrawal/problem-list-generator-Q8_0-GGUF:Q8_0
```

Lemonade

How to use samrawal/problem-list-generator-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull samrawal/problem-list-generator-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.problem-list-generator-Q8_0-GGUF-Q8_0

List all available models

lemonade list

samrawal/problem-list-generator-Q8_0-GGUF

About

problem-list-generator is an experimental local LLM trained to generate a list of active clinical problems from a History and Physical (H&P) section of a clinical note.

This is part of a small personal experiment to train small, fast, local language models that can assist clinicians when writing medical notes. It can be run completely offline, without any data leaving your local machine.

For more information on trying this out, please see the corresponding GitHub repository.

Technical Details

This model was finetuned using synthetic clinical data generated with Llama 3.1 405b. The model itself is a LORA finetune of Meta-Llama-3.1-8B-Instruct.

This repository contains a basic Python script to inference the model via Ollama.

Setup

Clone this repository
Download the GGUF model from here and place in same directory as the repo.
Add the model to Ollama: ollama create problemlist -f ProblemList.Modelfile
Run the Python script: python problemlist.py

Downloads last month: 6

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

8-bit

Model tree for samrawal/problem-list-generator-Q8_0-GGUF

Base model

samrawal/problem-list-generator

Quantized

(1)

this model