fix: model load for unsupported embedding models (#12311)

with #12181, there's now support for embeddings in ollama engine.
this is done by mutating the architecture and adding _embed when it
detects an embedding model. however this introduced a bug where if
an embedding model was run based on an existing ollama engine model
without an embedding implementation, e.g. llama4, it will pass the
initial arch support check but fail when actually loaded.

there's currently two entrypoints to creating a model. previously this
second entrypoint was necessary because calling model.New would also
load the model. since #11818, this is no longer th case so merge them
to reduce complexity

model/model.go

@@ -107,23 +107,12 @@ func New(modelPath string, params ml.BackendParams) (Model, error) {
 		return nil, err
 	}
 
-	arch := b.Config().Architecture()
-	if pooling.Type(b.Config().Uint("pooling_type")) != pooling.TypeNone {
-		arch = arch + "_embed"
-	}
-
-	f, ok := models[arch]
-	if !ok {
-		return nil, fmt.Errorf("unsupported model architecture %q", arch)
-	}
-
-	m, err := f(b.Config())
+	m, err := modelForArch(b.Config())
 	if err != nil {
 		return nil, err
 	}
 
 	base := Base{b: b, config: m.Config()}
-
 	v := reflect.ValueOf(m)
 	v.Elem().Set(populateFields(base, v.Elem()))
 	return m, nil
@@ -135,30 +124,38 @@ func NewTextProcessor(s string) (TextProcessor, error) {
 		return nil, err
 	}
 	defer r.Close()
+
 	meta, err := fsggml.Decode(r, -1)
 	if err != nil {
 		return nil, err
 	}
-	return getTextProcessor(meta.KV())
-}
 
-func getTextProcessor(kv fsggml.KV) (TextProcessor, error) {
-	arch := kv.Architecture()
-	f, ok := models[arch]
-	if !ok {
-		return nil, fmt.Errorf("unsupported model architecture %q", arch)
-	}
-	m, err := f(kv)
+	m, err := modelForArch(meta.KV())
 	if err != nil {
 		return nil, err
 	}
+
 	tp, ok := m.(TextProcessor)
 	if !ok {
-		return nil, fmt.Errorf("%v is not a TextProcessor", m)
+		return nil, ErrUnsupportedTokenizer
 	}
 	return tp, nil
 }
 
+func modelForArch(c fs.Config) (Model, error) {
+	arch := c.Architecture()
+	if pooling.Type(c.Uint("pooling_type")) != pooling.TypeNone {
+		arch = arch + "_embed"
+	}
+
+	f, ok := models[arch]
+	if !ok {
+		return nil, ErrUnsupportedModel
+	}
+
+	return f(c)
+}
+
 func populateFields(base Base, v reflect.Value, tags ...Tag) reflect.Value {
 	t := v.Type()
 

model/model_test.go

@@ -1,9 +1,9 @@
 package model
 
 import (
+	"errors"
 	"reflect"
 	"slices"
-	"strings"
 	"testing"
 
 	"github.com/google/go-cmp/cmp"
@@ -12,7 +12,6 @@ import (
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/ml/backend/ggml"
 	"github.com/ollama/ollama/ml/nn"
-	"github.com/ollama/ollama/model/input"
 )
 
 func TestParseTags(t *testing.T) {
@@ -148,39 +147,58 @@ func TestPopulateFieldsAlternateName(t *testing.T) {
 	}
 }
 
-func TestGetTextProcessor(t *testing.T) {
-	tp, err := getTextProcessor(fsggml.KV{})
-	if err == nil {
-		t.Error("expected error")
-	} else if !strings.Contains(err.Error(), "unsupported model architecture") {
-		t.Errorf("unexpected error: %v", err)
-	} else if tp != nil {
-		t.Error("expected nil tp")
+func TestModelForArch(t *testing.T) {
+	type fakeModel struct {
+		Model
 	}
 
-	models["dummy"] = func(fs.Config) (Model, error) {
-		return notTextProcessorModel{}, nil
+	type fakeEmbeddingModel struct {
+		Model
 	}
-	tp, err = getTextProcessor(fsggml.KV{"general.architecture": "dummy"})
-	if err == nil {
-		t.Error("expected error")
-	} else if !strings.Contains(err.Error(), "not a TextProcessor") {
-		t.Errorf("unexpected error: %v", err)
-	} else if tp != nil {
-		t.Error("expected nil tp")
+
+	models["model"] = func(c fs.Config) (Model, error) { return fakeModel{}, nil }
+	models["model_embed"] = func(c fs.Config) (Model, error) { return fakeEmbeddingModel{}, nil }
+
+	cases := []struct {
+		name   string
+		config fs.Config
+		want   any
+		err    error
+	}{
+		{
+			name: "model",
+			config: fsggml.KV{
+				"general.architecture": "model",
+			},
+			want: fakeModel{},
+		},
+		{
+			name: "embedding",
+			config: fsggml.KV{
+				"general.architecture": "model",
+				"model.pooling_type":   uint32(1),
+			},
+			want: fakeEmbeddingModel{},
+		},
+		{
+			name: "unsupported",
+			config: fsggml.KV{
+				"general.architecture": "unsupported",
+			},
+			err: ErrUnsupportedModel,
+		},
+	}
+
+	for _, tt := range cases {
+		t.Run(tt.name, func(t *testing.T) {
+			got, err := modelForArch(tt.config)
+			if !errors.Is(err, tt.err) {
+				t.Fatal(err)
+			}
+
+			if diff := cmp.Diff(tt.want, got); diff != "" {
+				t.Errorf("modelForArch() returned unexpected values (-want +got):\n%s", diff)
+			}
+		})
 	}
 }
-
-type notTextProcessorModel struct{}
-
-func (notTextProcessorModel) Forward(ml.Context, input.Batch) (ml.Tensor, error) {
-	panic("unimplemented")
-}
-
-func (notTextProcessorModel) Backend() ml.Backend {
-	panic("unimplemented")
-}
-
-func (notTextProcessorModel) Config() config {
-	panic("unimplemented")
-}