Add F16 and I2_S GGUF conversion for bitnet-embeddings 0.6B and 270M models#584
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Add F16 and I2_S GGUF conversion for bitnet-embeddings 0.6B and 270M models#584isHuangXin wants to merge 6 commits into
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…nversion - Add GGUF conversion tool for bitnet-embeddings-0.6b (safetensors -> F16/I2_S GGUF) - Add Qwen3 architecture support in llama.cpp submodule with per-projection RMSNorm - Add I2_S ternary quantization (2-bit packed -1/0/+1) for lossless precision - Add f16 norm weight support for correct embedding inference - Guard bitnet-lut-kernels.h include with TL1/TL2 preprocessor checks - Update llama.cpp submodule to dev-bitnet-embedding-0.6b branch - Document F16 (from multilingual-e5-0.6b) and I2_S (from bitnet-embeddings-0.6b) conversion process
…MAC LUT path - Add quantize_to_i2_s() for direct ternary-to-I2_S packing in conversion script - Support offline-quantized models (uint8 packed weights + weight_scale) - Fix weight_quant double-quantization bug for offline-quantized models - Fix I2_S scale computation to use first nonzero absolute value - Add I2_S ftype mapping and BitNetForCausalLM registration - Refactor ggml-bitnet-lut T-MAC wrapper with proper mul_mat implementation - Update llama.cpp submodule with I2_S ftype and 2B model type support
…nversion - Add LLM_ARCH_GEMMA3 in llama.cpp for gemma3_text model type (embedding scaling, GELU, post-attn/post-FFN norms, GQA) - Add GGUF conversion support for Gemma3-based 270m models (SPM tokenizer, RMSNorm w+1 offset, arch-specific tensor mapping) - Add tokenizer hash for multilingual-e5-0.6b-260311 - Add conversion documentation
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…ds, update Python requirement
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Summary
conversion scripts
Changes
quantization)
Test Plan