Expand description
Maps tabfm/src/pytorch/model.py state_dict keys (from torch.load(pytorch_model.bin),
after conversion to safetensors) to canonical GGUF tensor names.
There’s no pre-existing GGUF naming convention for this architecture family, so this module
defines one. Stack prefixes mirror the five weight-sharing sub-networks in TabFM.forward:
cell<-cell_embedder(per-cell Fourier embedding)colenc1<-col_embedder(SetTransformer, stage 1)colenc2<-col_embedder_2(SetTransformer, stage 2)rowenc1<-row_interactor(RoPE cross-column attention, stage 1)rowenc2<-row_interactor_2(RoPE cross-column attention, stage 2)icl<-icl_predictor(24-block in-context-learning attention)cls_tokensis a top-level parameter with no stack.
Column stacks nest two MultiheadAttentionBlocks per transformer block (mab1, mab2 —
induced-attention query/apply pair); row and ICL stacks have one attention+FFN sublayer per
block. Both share the same leaf naming for a block’s attention/FFN/norm weights.