Remove launch_massive_scale.sh - cleanup for OS launch

launch_massive_scale.sh

@@ -1,75 +0,0 @@
-#!/bin/bash
-#
-# BitTransformerLM Massive Scale Training Launcher
-# =================================================
-# 
-# Launches 1.21B parameter BitTransformerLM training across 4x NVIDIA L4 GPUs
-# with FSDP (Fully Sharded Data Parallel) for maximum efficiency.
-#
-
-set -e  # Exit on any error
-
-echo "🚀 BITTRANSFORMERLM MASSIVE SCALE TRAINING LAUNCHER"
-echo "=================================================="
-echo "Target: 680 MILLION parameters"
-echo "Hardware: 4x NVIDIA L4 GPUs (23GB each)"
-echo "Dataset: WikiText-103 + Real Corpus Data"
-echo "Architecture: Reversible Transformer with Safety Telemetry"
-echo ""
-
-# Set environment variables
-export CUDA_VISIBLE_DEVICES=0,1,2,3
-export PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
-export NCCL_DEBUG=INFO
-export NCCL_TREE_THRESHOLD=0
-
-# Set HuggingFace token
-export HF_TOKEN="${HF_TOKEN:-your-token-here}"
-
-# Change to BitTransformerLM directory
-cd /data/BitTransformerLM/BitTransformerLM
-
-# Create checkpoint directory
-mkdir -p /data/checkpoints
-
-# Check GPU availability
-echo "🔍 Checking GPU availability..."
-python -c "
-import torch
-print(f'CUDA Available: {torch.cuda.is_available()}')
-print(f'GPU Count: {torch.cuda.device_count()}')
-for i in range(torch.cuda.device_count()):
-    print(f'  GPU {i}: {torch.cuda.get_device_name(i)} ({torch.cuda.get_device_properties(i).total_memory / 1024**3:.1f}GB)')
-"
-
-echo ""
-echo "📊 Model Configuration Preview:"
-echo "  • Parameters: 679,630,848 (680M)" 
-echo "  • d_model: 1536"
-echo "  • Layers: 24 (reversible)"
-echo "  • Attention Heads: 24"
-echo "  • Feed Forward: 6144"
-echo "  • Sequence Length: 2048"
-echo "  • Batch Size: 4 per GPU (16 total)"
-echo "  • Gradient Accumulation: 32 steps"
-echo "  • Effective Batch Size: 512"
-echo ""
-
-echo "🎯 Starting distributed training..."
-echo "   Use Ctrl+C to stop training safely"
-echo ""
-
-# Launch distributed training with torchrun
-torchrun \
-    --nproc_per_node=4 \
-    --master_port=29500 \
-    --nnodes=1 \
-    --node_rank=0 \
-    massive_scale_training.py \
-    --world-size 4 \
-    --port 29500
-
-echo ""
-echo "🏁 Training completed!"
-echo "Check /data/checkpoints/ for saved models"
-echo "Check /data/massive_scale_training.log for detailed logs"