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Distributed Training Enhancements: Proper NCCL/Gloo backend selection Distributed timeout handling Rank-aware input broadcasting Graceful process group cleanup Error Handling & Validation Comprehensive path validation Config schema validation Tokenization error handling Batch processing safeguards CUDA OOM fallback handling Generation Improvements: Top-k sampling support Repetition penalty Dynamic sequence length management Progress tracking with tqdm Sequence truncation warnings Performance Optimizations: Device-aware tensor placement Batch tokenization Memory-efficient generation loop Model parallelism support User Experience: Interactive mode enhancements: Command history Input validation Graceful exit handling Batch processing: Progress tracking Error resilience Clean output formatting Code Quality: Type hints throughout Configurable constants Modular architecture Docstrings with examples Logging integration Safety Features: Tokenizer trust_remote_code handling Config validation Input sanitization Resource cleanup guarantees |
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.. | ||
configs | ||
convert.py | ||
fp8_cast_bf16.py | ||
generate.py | ||
kernel.py | ||
model.py | ||
requirements.txt |