german-moe-gpt-v8-pretrained / requirements.txt
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# German MoE GPT v6 - Requirements
# Environment: nano_moe (Conda)
# Python: 3.10+
# CUDA: 12.4
# ============================================================================
# CRITICAL: PyTorch Installation
# ============================================================================
# IMPORTANT: Install PyTorch FIRST with CUDA support!
# DO NOT use pip for PyTorch on Windows - use conda instead:
#
# conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia
#
# Or from PyTorch website (pip with CUDA):
# pip install torch==2.6.0+cu124 torchvision==0.21.0+cu124 torchaudio==2.6.0+cu124 --index-url https://download.pytorch.org/whl/cu124
#
# Current installed versions:
# torch==2.6.0+cu124
# torchvision==0.21.0+cu124
# torchaudio==2.6.0+cu124
# ============================================================================
# Core ML Libraries (install AFTER PyTorch!)
transformers==4.56.1
datasets==4.0.0
accelerate==1.10.1
# Training & Monitoring
tensorboard==2.20.0
tensorboard-data-server==0.7.2
# Tokenization
tokenizers==0.22.0
tiktoken==0.11.0
# Data Processing
numpy==1.26.4
pandas==2.3.2
pyarrow==21.0.0
# Utilities
tqdm==4.67.1
safetensors==0.6.2
huggingface-hub==0.34.4
regex==2025.9.1
fsspec==2025.3.0
dill==0.3.8
multiprocess==0.70.16
xxhash==3.5.0
# Performance (Windows CUDA)
triton-windows==3.2.0.post19 # Optimized kernels for CUDA
# Configuration & Logging
PyYAML==6.0.2
python-dotenv==1.0.1
requests==2.32.5
httpx[http2]==0.27.0
# Optional: Weights & Biases (uncomment if needed)
# wandb>=0.15.0
# ============================================================================
# Installation Instructions
# ============================================================================
#
# STEP 1: Create conda environment
# conda create -n nano_moe python=3.10
# conda activate nano_moe
#
# STEP 2: Install PyTorch with CUDA 12.4
# conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia
#
# STEP 3: Install remaining dependencies
# pip install -r requirements.txt --no-deps
# (--no-deps prevents pip from reinstalling PyTorch!)
#
# STEP 4: Verify installation
# python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"
#
# ============================================================================
# Notes
# ============================================================================
#
# - DO NOT install PyTorch via pip requirements.txt on Windows!
# It will install CPU version or wrong CUDA version
#
# - triton-windows only works on Windows with CUDA
# On Linux, use: triton>=2.0.0
#
# - datasets 4.0.0 has breaking changes from 2.x
# Use load_from_disk() / save_to_disk() for eval dataset
#
# - transformers 4.56.1 is compatible with our custom MoE implementation
#
# ============================================================================