Phase 14: GGUF Model Optimizations#22
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This commit implements deep integration with the GGUF file format, enabling direct loading of GGUF tensors into the Ternary Fabric. Key changes: - Added `src/pytfmbs/gguf.py`: A robust GGUF v2/v3 reader with support for metadata (KV) and Q4_0/F32 tensor dequantization. - Updated `src/pytfmbs/__init__.py`: Exposed `GGUFReader` and `load_gguf_tensor` API. - Added `docs/14_GGUF.md`: Documentation for GGUF integration. - Updated `docs/ROADMAP.md`: Marked Phase 14 as complete. - Added `tools/gguf_mock.py`: Utility to generate mock GGUF files. - Added `tests/test_gguf.py`: Verification test suite for GGUF loading. These changes allow TFMBS to act as a transparent acceleration layer for existing LLM models in GGUF format by automatically converting quantized weights to the hardware-native ternary format. Co-authored-by: t81dev <207451414+t81dev@users.noreply.github.com>
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Phase 14 of the roadmap (GGUF Model Optimizations) has been implemented. This includes a native GGUF reader in Python, support for Q4_0 dequantization, and a direct loading API that handles the conversion from quantized GGUF weights to ternary PT-5 format for the Fabric. Documentation and tests are included.
PR created automatically by Jules for task 168150934176355900 started by @t81dev