llm: Use first layer as memory buffer in estimation

This is a partial revert of 0478d440 "Fixed over vram allcation dure to
small initial layer sizes."

Previously we used the size of the first layer as an extra reserved
amount of space to buffer our memory estimates. The above commit
changed this to use the largest layer. However, this had performance
impacts on more models than the original commit was trying to fix.

There is just a heuristic without an ideal solution so this goes back
to the historic behavior.

Fixes: #10765, #10756, #10752, #10726

llm/memory.go

 package llm
 
 import (
-	"cmp"
 	"fmt"
 	"log/slog"
-	"maps"
 	"os"
-	"slices"
 	"strconv"
 	"strings"
 
@@ -125,10 +122,12 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 	}
 
 	layers := f.Tensors().GroupLayers()
-	// add one layer (chosing the max layer) worth of memory as a buffer
-	layerSize = slices.MaxFunc(slices.Collect(maps.Values(layers)), func(a, b ggml.Layer) int {
-		return cmp.Compare(a.Size(), b.Size())
-	}).Size()
+	// add one layer worth of memory as a buffer
+	if blk0, ok := layers["blk.0"]; ok {
+		layerSize = blk0.Size()
+	} else {
+		slog.Warn("model missing blk.0 layer size")
+	}
 
 	var kvct string
 	if envconfig.FlashAttention() &&