fix: improve pytorch model initialization to prevent meta tensor issues#180
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nicoloboschi merged 3 commits intomainfrom Jan 20, 2026
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fix: improve pytorch model initialization to prevent meta tensor issues#180nicoloboschi merged 3 commits intomainfrom
nicoloboschi merged 3 commits intomainfrom
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When accelerate is installed but no GPU is available, transformers can incorrectly use lazy loading (meta tensors) which fails when sentence-transformers tries to move the model to a device. The fix checks hardware and installed packages to determine the right loading strategy: - GPU available: device=None, device_map=None (auto-detect GPU) - No GPU + accelerate: device='cpu', device_map='cpu' (force CPU loading) - No GPU + no accelerate: device='cpu', device_map=None (normal CPU) 🤖 Generated with [Claude Code](https://claude.com/claude-code)
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When pytest-xdist runs multiple workers in parallel, they all try to load models from the HuggingFace cache simultaneously, causing race conditions and intermittent meta tensor errors. Added filelock around embeddings and cross_encoder initialization in conftest.py, similar to how pg0 database setup is serialized. Models are now pre-initialized in the fixture before being passed to tests. 🤖 Generated with [Claude Code](https://claude.com/claude-code)
Extend GPU detection to include Apple MPS backend in addition to CUDA. This ensures macOS users with Apple Silicon use MPS acceleration instead of being incorrectly routed to the CPU fallback path.
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