Upload folder using huggingface_hub

.gitattributes

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README.md

@@ -1,3 +1,75 @@
+# PyTorch Python 3.10 Wheel Collection
+
+Complete PyTorch ML stack with all dependencies - no conflicts, easy installation.
+
+## 📋 What's Included
+
+- **Python:** 3.10 compatible
+- **PyTorch:** 2.7.1 + CUDA 12.6
+- **Transformers:** 4.52.3
+- **NumPy:** 1.26.4 (compatible version)
+- **SciPy:** 1.15.2
+- **All Dependencies:** 80+ wheels, fully tested together
+
+## 🚀 Installation (Super Easy!)
+
+**One command installation from HuggingFace:**
+
+```bash
+# Download and install everything
+from huggingface_hub import snapshot_download
+import subprocess
+import os
+
+# Download all wheels
+repo_path = snapshot_download(repo_id="RDHub/pytorch_python_310")
+wheel_path = os.path.join(repo_path, "lib_wheel")
+
+# Install all wheels
+subprocess.run(["pip", "install"] + [f"{wheel_path}/*.whl"], shell=True)
+```
+
+**Or manually:**
+
+```bash
+# 1. Download repository
+git clone https://huggingface.co/RDHub/pytorch_python_310
+
+# 2. Install everything
+cd pytorch_python_310
+pip install lib_wheel/*.whl
+
+# 3. Test (optional)
+python -c "import torch; print(f'PyTorch {torch.__version__} - CUDA: {torch.cuda.is_available()}')"
+```
+
+## ✅ Key Versions
+
+| Package | Version | Python |
+|---------|---------|---------|
+| PyTorch | 2.7.1 | 3.10 |
+| Transformers | 4.52.3 | 3.10 |
+| NumPy | 1.26.4 | 3.10 |
+| CUDA | 12.6 | - |
+
+## 🎯 Use Cases
+
+Perfect for:
+- Machine Learning projects
+- Large Language Model training
+- Computer Vision
+- Audio processing
+- Research environments
+
+## 📝 Notes
+
+- **No dependency conflicts** - all versions tested together
+- **Offline ready** - no internet needed after download
+- **CUDA included** - ready for GPU training
+- **Linux x86_64** compatible
+
 ---
-license: mit
----
+
+**Repository Size:** ~2GB  
+**Total Packages:** 80+ wheels  
+**Tested:** Ubuntu 22.04, Python 3.10

install.sh

@@ -0,0 +1,100 @@
+#!/bin/bash
+
+# PyTorch Wheel Installation Script
+# This script installs PyTorch and all compatible dependencies from local wheels
+
+set -e  # Exit on any error
+
+WHEEL_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+echo "Installing PyTorch and dependencies from: $WHEEL_DIR"
+
+# Check if we're in the correct directory
+if [ ! -f "$WHEEL_DIR/torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl" ]; then
+    echo "Error: PyTorch wheel not found in $WHEEL_DIR"
+    echo "Please ensure you're running this script from the pytorch_wheel directory"
+    exit 1
+fi
+
+echo "Step 1: Installing core Python packages..."
+pip install "$WHEEL_DIR"/setuptools-*.whl "$WHEEL_DIR"/wheel-*.whl "$WHEEL_DIR"/pip-*.whl || true
+
+echo "Step 2: Installing basic dependencies..."
+pip install "$WHEEL_DIR"/six-*.whl "$WHEEL_DIR"/typing_extensions-*.whl "$WHEEL_DIR"/packaging-*.whl
+
+echo "Step 3: Installing NumPy (compatible version)..."
+pip install "$WHEEL_DIR"/numpy-1.26.4-*.whl
+
+echo "Step 4: Installing core utilities..."
+pip install "$WHEEL_DIR"/tqdm-*.whl "$WHEEL_DIR"/requests-*.whl "$WHEEL_DIR"/filelock-*.whl "$WHEEL_DIR"/regex-*.whl
+
+echo "Step 5: Installing NVIDIA CUDA libraries..."
+pip install "$WHEEL_DIR"/nvidia_*.whl
+
+echo "Step 6: Installing PyTorch ecosystem..."
+pip install "$WHEEL_DIR"/sympy-*.whl "$WHEEL_DIR"/mpmath-*.whl "$WHEEL_DIR"/networkx-*.whl "$WHEEL_DIR"/triton-*.whl
+
+echo "Step 7: Installing PyTorch..."
+pip install "$WHEEL_DIR"/torch-*.whl "$WHEEL_DIR"/torchaudio-*.whl
+
+echo "Step 8: Installing HuggingFace and tokenizers..."
+pip install "$WHEEL_DIR"/safetensors-*.whl "$WHEEL_DIR"/tokenizers-*.whl "$WHEEL_DIR"/huggingface_hub-*.whl "$WHEEL_DIR"/fsspec-*.whl
+
+echo "Step 9: Installing ML libraries..."
+pip install "$WHEEL_DIR"/transformers-*.whl "$WHEEL_DIR"/accelerate-*.whl "$WHEEL_DIR"/peft-*.whl "$WHEEL_DIR"/datasets-*.whl
+
+echo "Step 10: Installing scientific libraries..."
+pip install "$WHEEL_DIR"/scipy-*.whl "$WHEEL_DIR"/librosa-*.whl "$WHEEL_DIR"/opencv_python-*.whl
+
+echo "Step 11: Installing JSON/Schema handling..."
+pip install "$WHEEL_DIR"/rpds_py-*.whl "$WHEEL_DIR"/referencing-*.whl "$WHEEL_DIR"/jsonschema_specifications-*.whl "$WHEEL_DIR"/jsonschema-*.whl
+
+echo "Step 12: Installing system utilities..."
+pip install "$WHEEL_DIR"/attrs-*.whl "$WHEEL_DIR"/distro-*.whl "$WHEEL_DIR"/tomli-*.whl "$WHEEL_DIR"/platformdirs-*.whl "$WHEEL_DIR"/tornado-*.whl "$WHEEL_DIR"/monotonic-*.whl
+
+echo "Step 13: Installing additional utilities..."
+pip install "$WHEEL_DIR"/babel-*.whl "$WHEEL_DIR"/fs-*.whl "$WHEEL_DIR"/appdirs-*.whl "$WHEEL_DIR"/more_itertools-*.whl
+
+echo "Step 14: Installing PyTorch Lightning..."
+pip install "$WHEEL_DIR"/lightning_utilities-*.whl "$WHEEL_DIR"/pytorch_lightning-*.whl
+
+echo "Step 15: Installing Jupyter support..."
+pip install "$WHEEL_DIR"/nbconvert-*.whl
+
+echo "Step 16: Installing OpenTelemetry (compatible versions)..."
+pip install "$WHEEL_DIR"/opentelemetry_semantic_conventions-*.whl "$WHEEL_DIR"/opentelemetry_api-*.whl "$WHEEL_DIR"/opentelemetry_sdk-*.whl "$WHEEL_DIR"/opentelemetry_util_http-*.whl "$WHEEL_DIR"/opentelemetry_instrumentation-*.whl "$WHEEL_DIR"/opentelemetry_instrumentation_asgi-*.whl
+
+echo "Step 17: Installing data handling..."
+pip install "$WHEEL_DIR"/pydantic_settings-*.whl "$WHEEL_DIR"/dataclasses_json-*.whl "$WHEEL_DIR"/pypdf-*.whl
+
+echo "Step 18: Installing API clients..."
+pip install "$WHEEL_DIR"/httpx-*.whl "$WHEEL_DIR"/openai-*.whl
+
+echo "Step 19: Installing CLI utilities..."
+pip install "$WHEEL_DIR"/decorator-*.whl "$WHEEL_DIR"/typer-*.whl
+
+echo "Step 20: Installing remaining packages..."
+pip install "$WHEEL_DIR"/keyring-*.whl "$WHEEL_DIR"/virtualenv-*.whl "$WHEEL_DIR"/protobuf-*.whl "$WHEEL_DIR"/mako-*.whl "$WHEEL_DIR"/markdown-*.whl "$WHEEL_DIR"/lxml-*.whl "$WHEEL_DIR"/chardet-*.whl "$WHEEL_DIR"/tensorboard-*.whl
+
+echo ""
+echo "Installation completed successfully!"
+echo ""
+echo "Testing imports..."
+python -c "
+import torch
+import numpy
+import transformers
+import accelerate
+import peft
+import datasets
+import scipy
+import librosa
+print('✅ All major packages imported successfully!')
+print(f'PyTorch version: {torch.__version__}')
+print(f'CUDA available: {torch.cuda.is_available()}')
+if torch.cuda.is_available():
+    print(f'CUDA device count: {torch.cuda.device_count()}')
+"
+
+echo ""
+echo "🎉 PyTorch installation with all compatible dependencies completed!"
+echo "No more dependency conflicts should occur."

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