Add comprehensive installation guide with troubleshooting

INSTALLATION_GUIDE.md

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+# PyTorch Python 3.10 Installation Guide
+
+## 🚀 Quick Start
+
+### Option 1: Automated Setup (Recommended)
+
+```bash
+# 1. Create conda environment
+conda create -n pytorch_env python=3.10
+conda activate pytorch_env
+
+# 2. Download repository
+git clone https://huggingface.co/RDHub/pytorch_python_310
+cd pytorch_python_310
+
+# 3. Install all packages
+pip install -r lib_wheel/requirements.txt --find-links lib_wheel --no-index
+
+# 4. Set up CUDA libraries
+bash setup_cuda_libs.sh
+
+# 5. Test installation
+python -c "import torch; print(f'PyTorch {torch.__version__} - CUDA: {torch.cuda.is_available()}')"
+```
+
+### Option 2: Manual Setup
+
+```bash
+# 1. Install packages
+pip install -r lib_wheel/requirements.txt --find-links lib_wheel --no-index
+
+# 2. Create CUDA library activation script
+mkdir -p $CONDA_PREFIX/etc/conda/activate.d
+cat > $CONDA_PREFIX/etc/conda/activate.d/pytorch_cuda_libs.sh << 'EOF'
+#!/bin/bash
+NVIDIA_LIB_PATH=$(find $CONDA_PREFIX -path "*/nvidia/*/lib" -type d 2>/dev/null | tr '\n' ':')
+CUSPARSELT_LIB_PATH=$(find $CONDA_PREFIX -path "*/cusparselt/lib" -type d 2>/dev/null | tr '\n' ':')
+export LD_LIBRARY_PATH="${NVIDIA_LIB_PATH}${CUSPARSELT_LIB_PATH}${LD_LIBRARY_PATH}"
+EOF
+chmod +x $CONDA_PREFIX/etc/conda/activate.d/pytorch_cuda_libs.sh
+
+# 3. Reactivate environment
+conda deactivate && conda activate your_env_name
+```
+
+## ✅ What's Included
+
+- **PyTorch 2.7.1** with CUDA 12.6 support
+- **Transformers 4.52.3** for HuggingFace models
+- **NumPy 2.0.2** (compatible with OpenCV)
+- **OpenCV 4.10.0** for computer vision
+- **80+ compatible packages** tested together
+- **NVIDIA CUDA libraries** (12.6.x series)
+
+## 🧪 Testing Your Installation
+
+```python
+import torch
+import transformers
+import numpy as np
+import cv2
+
+# Test PyTorch CUDA
+print(f"PyTorch: {torch.__version__}")
+print(f"CUDA Available: {torch.cuda.is_available()}")
+if torch.cuda.is_available():
+    print(f"GPU: {torch.cuda.get_device_name(0)}")
+
+# Test basic operations
+x = torch.randn(100, 100).cuda()
+y = torch.matmul(x, x.T)
+print("✅ GPU tensor operations working!")
+
+# Test transformers
+from transformers import AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+print("✅ Transformers working!")
+
+print(f"NumPy: {np.__version__}")
+print(f"OpenCV: {cv2.__version__}")
+```
+
+## 🔧 Troubleshooting
+
+### Issue: "libcufile.so.0: cannot open shared object file"
+
+**Solution:** Run the CUDA setup script:
+```bash
+bash setup_cuda_libs.sh
+conda deactivate && conda activate your_env_name
+```
+
+### Issue: "libcusparseLt.so.0: cannot open shared object file"
+
+**Solution:** Ensure all NVIDIA packages are installed:
+```bash
+pip install --force-reinstall lib_wheel/nvidia_cusparselt_cu12-*.whl
+pip install --force-reinstall lib_wheel/nvidia_cufile_cu12-*.whl
+```
+
+### Issue: OpenCV + NumPy compatibility errors
+
+**Solution:** Use the exact versions provided:
+```bash
+pip install --force-reinstall lib_wheel/numpy-2.0.2-*.whl
+pip install --force-reinstall lib_wheel/opencv_python-4.10.0.84-*.whl
+```
+
+## 📋 System Requirements
+
+- **OS:** Linux x86_64 (Ubuntu 22.04+ recommended)
+- **Python:** 3.10
+- **CUDA:** Compatible with 12.2+ (12.6 optimal)
+- **Conda:** Required for library path management
+- **Storage:** ~2GB for all wheels
+
+## 🎯 Verified Configurations
+
+✅ **Ubuntu 22.04** + Python 3.10 + CUDA 12.2  
+✅ **Ubuntu 22.04** + Python 3.10 + CUDA 12.6  
+✅ **RTX 4090** + CUDA 12.6  
+✅ **Conda environments**  
+
+## 🔗 Resources
+
+- **Repository:** https://huggingface.co/RDHub/pytorch_python_310
+- **PyTorch Docs:** https://pytorch.org/docs/
+- **CUDA Toolkit:** https://developer.nvidia.com/cuda-toolkit