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PEFT
gemma4
medical
healthcare
community-health
lora
unsloth
who-imci
saheli
fhir
function-calling
thinking-mode
semantic-rag
muthuk1's picture
Upload setup.sh
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#!/bin/bash
# SAHELI - Quick Start Guide
# Run this script to set up and launch everything
echo "============================================"
echo " SAHELI - Smart Adaptive Health Engine"
echo " Quick Start Setup"
echo "============================================"
# 1. Install dependencies for training
echo ""
echo "[1/3] Installing training dependencies..."
pip install -U unsloth trl torch datasets trackio accelerate transformers bitsandbytes peft xformers
# 2. Login to HuggingFace
echo ""
echo "[2/3] Logging into HuggingFace..."
echo "Please run: huggingface-cli login"
echo "Or set HF_TOKEN environment variable"
# 3. Launch training
echo ""
echo "[3/3] Launching training..."
echo "Run: python train_saheli.py"
echo ""
echo "============================================"
echo " After training completes, your models will be at:"
echo " - LoRA: https://huggingface.co/muthuk1/saheli-gemma4-e4b-medical"
echo " - Merged: https://huggingface.co/muthuk1/saheli-gemma4-e4b-medical-merged"
echo " - GGUF: https://huggingface.co/muthuk1/saheli-gemma4-e4b-medical-gguf"
echo ""
echo " Live Demo: https://huggingface.co/spaces/muthuk1/saheli-community-health-ai"
echo "============================================"
echo ""
echo "For local deployment with Ollama:"
echo " ollama create saheli -f Modelfile"
echo " ollama run saheli"