Image-Text-to-Text
Transformers
ONNX
Safetensors
English
medical
chest-xray
radiology
clip
blip
multimodal
cpu
Instructions to use GAD-Research-Lab/MedicalAI-Light-Weight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GAD-Research-Lab/MedicalAI-Light-Weight with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="GAD-Research-Lab/MedicalAI-Light-Weight")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GAD-Research-Lab/MedicalAI-Light-Weight", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GAD-Research-Lab/MedicalAI-Light-Weight with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GAD-Research-Lab/MedicalAI-Light-Weight" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GAD-Research-Lab/MedicalAI-Light-Weight", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GAD-Research-Lab/MedicalAI-Light-Weight
- SGLang
How to use GAD-Research-Lab/MedicalAI-Light-Weight with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "GAD-Research-Lab/MedicalAI-Light-Weight" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GAD-Research-Lab/MedicalAI-Light-Weight", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "GAD-Research-Lab/MedicalAI-Light-Weight" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GAD-Research-Lab/MedicalAI-Light-Weight", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GAD-Research-Lab/MedicalAI-Light-Weight with Docker Model Runner:
docker model run hf.co/GAD-Research-Lab/MedicalAI-Light-Weight
File size: 4,023 Bytes
e93bfbd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 | <#
.SYNOPSIS
One-click launcher for MedicalAI - Light Weight
.DESCRIPTION
Checks for Python, sets up venv, installs deps, and launches the app.
Double-click this file or run: powershell -File launch.ps1
#>
$ErrorActionPreference = "Stop"
$ProjectRoot = Split-Path -Parent $MyInvocation.MyCommand.Path
Set-Location $ProjectRoot
$Host.UI.RawUI.WindowTitle = "MedicalAI - Light Weight"
# ββ Check Python ββ
$python = $null
foreach ($cmd in @("python", "python3", "py")) {
try {
$v = & $cmd --version 2>&1
if ($v -match "Python 3\.(1[0-9]|[0-9]+)") {
$python = $cmd
break
}
} catch {}
}
if (-not $python) {
Write-Host "Python 3.10+ is required but not found." -ForegroundColor Red
Write-Host "Download from: https://www.python.org/downloads/" -ForegroundColor Yellow
Write-Host "Make sure to check 'Add Python to PATH' during installation." -ForegroundColor Yellow
Read-Host "Press Enter to exit"
exit 1
}
Write-Host "Using: $(& $python --version)" -ForegroundColor Green
# ββ Virtual Environment ββ
$venvPath = Join-Path $ProjectRoot ".venv"
if (-not (Test-Path $venvPath)) {
Write-Host "Creating virtual environment..." -ForegroundColor Cyan
& $python -m venv $venvPath
if (-not $?) { throw "Failed to create venv" }
}
# ββ Activate ββ
$activate = Join-Path $venvPath "Scripts\Activate.ps1"
. $activate
# ββ Install Dependencies ββ
$reqPath = Join-Path $ProjectRoot "requirements.txt"
if (Test-Path $reqPath) {
Write-Host "Installing dependencies..." -ForegroundColor Cyan
pip install -q -r $reqPath 2>&1 | Out-Null
if (-not $?) {
Write-Host "Retrying with full output..." -ForegroundColor Yellow
pip install -r $reqPath
}
}
# ββ Check / Generate Default Models ββ
$defaultClassifier = Join-Path $ProjectRoot "models\default\fusion_classifier.onnx"
$checkpoint = Join-Path $ProjectRoot "checkpoints\fusion_model.pth"
$onnxFull = Join-Path $ProjectRoot "checkpoints\onnx_full\fusion_full.onnx"
if ((-not (Test-Path $checkpoint)) -and (-not (Test-Path $onnxFull)) -and (-not (Test-Path $defaultClassifier))) {
Write-Host "No models found. Generating default models..." -ForegroundColor Yellow
python setup_default.py
Write-Host "Default models generated. The app will work immediately." -ForegroundColor Green
}
if (Test-Path $checkpoint) {
Write-Host "Trained model found." -ForegroundColor Green
} elseif (Test-Path $onnxFull) {
Write-Host "ONNX pipeline found." -ForegroundColor Green
} elseif (Test-Path $defaultClassifier) {
Write-Host "Default model found. Train a proper model for accurate results." -ForegroundColor Yellow
}
# ββ Ask how to launch ββ
Write-Host ""
Write-Host "MedicalAI - Light Weight" -ForegroundColor Cyan
Write-Host "========================" -ForegroundColor Cyan
Write-Host "1) Web UI (recommended - opens in browser)"
Write-Host "2) Command-line interface (CLI)"
Write-Host "3) API Server (for website/app integration)"
Write-Host ""
$choice = Read-Host "Select (1, 2, or 3)"
if ($choice -eq "2") {
Write-Host "Launching CLI..." -ForegroundColor Green
python run.py
} elseif ($choice -eq "3") {
# Ensure API deps are installed
try {
Import-Module python -ErrorAction Stop
python -c "import fastapi" 2>$null
} catch {
Write-Host "Installing API dependencies..." -ForegroundColor Cyan
python -m pip install "fastapi[standard]" uvicorn 2>&1 | Out-Null
}
Write-Host "Launching API server on http://127.0.0.1:8000 ..." -ForegroundColor Green
Write-Host "Your website can connect to: http://127.0.0.1:8000/api" -ForegroundColor Yellow
python quantization.py --mode serve-api
} else {
Write-Host "Launching web UI..." -ForegroundColor Green
python web_ui.py
}
# ββ Keep window open on crash ββ
if (-not $?) {
Write-Host "App exited with error. Press Enter to close." -ForegroundColor Red
Read-Host
}
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