fix: correct conv1d dimension squeeze for SSM architectures

After reverseShape, PyTorch conv1d [out, 1, kernel] becomes GGML [kernel, 1, out].
The squeeze was checking dims[2]==1 (out_channels, never 1) instead of dims[1]==1,
causing 3D tensors that trigger GGML_ASSERT(ggml_is_matrix) in llama.cpp.

Made-with: Cursor

Author: ganisback

internal/convert/arch_hybrid.go

@@ -71,9 +71,9 @@ func (c *hybridConverter) ConvertTensors(w *ggufWriter, sources []tensorSource,
 		srcCopy := src
 		idx := i
 
-		// Conv1d squeeze for SSM layers
-		if strings.Contains(hfName, "conv1d") && len(dims) == 3 && dims[2] == 1 {
-			dims = dims[:2]
+		// Conv1d squeeze for SSM layers. PyTorch [out, 1, k] → GGML [k, 1, out] → [k, out].
+		if strings.Contains(hfName, "conv1d") && len(dims) == 3 && dims[1] == 1 {
+			dims = []uint64{dims[0], dims[2]}
 		}
 
 		ggufName := nameMapper(hfName)

internal/convert/arch_mamba.go

@@ -82,9 +82,9 @@ func (c *mambaConverter) ConvertTensors(w *ggufWriter, sources []tensorSource, c
 			continue
 		}
 
-		// Conv1d squeeze
-		if strings.Contains(ggufName, "ssm_conv1d") && len(dims) == 3 && dims[2] == 1 {
-			dims = dims[:2]
+		// Conv1d squeeze. PyTorch [out, 1, k] → GGML [k, 1, out] → [k, out].
+		if strings.Contains(ggufName, "ssm_conv1d") && len(dims) == 3 && dims[1] == 1 {
+			dims = []uint64{dims[0], dims[2]}
 		}
 
 		outputType := chooseOutputTypeForSSM(ggufName, ggmlType, len(src.shape))
@@ -215,9 +215,9 @@ func (c *mamba2Converter) ConvertTensors(w *ggufWriter, sources []tensorSource,
 		dims := reverseShape(src.shape)
 		ggufName := nameMapper(hfName)
 
-		// Conv1d squeeze
-		if strings.Contains(ggufName, "ssm_conv1d") && len(dims) == 3 && dims[2] == 1 {
-			dims = dims[:2]
+		// Conv1d squeeze. PyTorch [out, 1, k] → GGML [k, 1, out] → [k, out].
+		if strings.Contains(ggufName, "ssm_conv1d") && len(dims) == 3 && dims[1] == 1 {
+			dims = []uint64{dims[0], dims[2]}
 		}
 
 		// SSM_A and SSM_D: unsqueeze (add trailing dim=1)
@@ -353,8 +353,8 @@ func (c *jambaConverter) ConvertTensors(w *ggufWriter, sources []tensorSource, c
 		dims := reverseShape(src.shape)
 		ggufName := nameMapper(hfName)
 
-		if strings.Contains(ggufName, "ssm_conv1d") && len(dims) == 3 && dims[2] == 1 {
-			dims = dims[:2]
+		if strings.Contains(ggufName, "ssm_conv1d") && len(dims) == 3 && dims[1] == 1 {
+			dims = []uint64{dims[0], dims[2]}
 		}
 
 		outputType := chooseOutputTypeForSSM(ggufName, ggmlType, len(src.shape))

internal/convert/arch_qwen35.go

@@ -34,9 +34,9 @@ func (c *qwen35Converter) ConvertTensors(w *ggufWriter, sources []tensorSource,
 		srcCopy := src
 		idx := i
 
-		// Conv1d weights: squeeze trailing dim=1.
-		if strings.Contains(hfName, "conv1d") && len(dims) == 3 && dims[2] == 1 {
-			dims = dims[:2]
+		// Conv1d weights: squeeze middle dim=1. PyTorch [out, 1, k] → GGML [k, 1, out] → [k, out].
+		if strings.Contains(hfName, "conv1d") && len(dims) == 3 && dims[1] == 1 {
+			dims = []uint64{dims[0], dims[2]}
 		}
 
 		ggufName := nameMapper(hfName)