fix token type

fs/config.go

@@ -8,6 +8,6 @@ type Config interface {
 	Bool(string, ...bool) bool
 
 	Strings(string, ...[]string) []string
-	Uints(string, ...[]uint32) []uint32
+	Ints(string, ...[]int32) []int32
 	Floats(string, ...[]float32) []float32
 }

fs/ggml/ggml.go

@@ -108,6 +108,10 @@ func (kv KV) Strings(key string, defaultValue ...[]string) []string {
 	return keyValue(kv, key, &array[string]{}).values
 }
 
+func (kv KV) Ints(key string, defaultValue ...[]int32) []int32 {
+	return keyValue(kv, key, &array[int32]{}).values
+}
+
 func (kv KV) Uints(key string, defaultValue ...[]uint32) []uint32 {
 	return keyValue(kv, key, &array[uint32]{}).values
 }
@@ -124,11 +128,18 @@ func (kv KV) OllamaEngineRequired() bool {
 }
 
 type valueTypes interface {
-	string | uint32 | uint64 | float32 | bool |
-		*array[string] | *array[uint32] | *array[uint64] | *array[float32] | *array[bool]
+	uint8 | int8 | uint16 | int16 |
+		uint32 | int32 | uint64 | int64 |
+		string | float32 | float64 | bool
+}
+
+type arrayValueTypes interface {
+	*array[uint8] | *array[int8] | *array[uint16] | *array[int16] |
+		*array[uint32] | *array[int32] | *array[uint64] | *array[int64] |
+		*array[string] | *array[float32] | *array[float64] | *array[bool]
 }
 
-func keyValue[T valueTypes](kv KV, key string, defaultValue ...T) T {
+func keyValue[T valueTypes | arrayValueTypes](kv KV, key string, defaultValue ...T) T {
 	if !strings.HasPrefix(key, "tokenizer.") && !strings.HasPrefix(key, "general.") {
 		key = kv.Architecture() + "." + key
 	}
@@ -450,9 +461,9 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 	case "mllama":
 		var visionTokens, tiles uint64 = 1601, 4
 
-		crossAttentionLayers := f.KV().Uints("attention.cross_attention_layers")
+		crossAttentionLayers := f.KV().Ints("attention.cross_attention_layers")
 		for i := range kv {
-			if slices.Contains(crossAttentionLayers, uint32(i)) {
+			if slices.Contains(crossAttentionLayers, int32(i)) {
 				kv[i] = headsKV * (embeddingHeadsK + embeddingHeadsV) *
 					4 * // sizeof(float32)
 					visionTokens *

model/models/gemma2/model.go

@@ -42,7 +42,7 @@ func New(c fs.Config) (model.Model, error) {
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
-				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
 				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
 			},

model/models/gemma3/model.go

@@ -59,7 +59,7 @@ func New(c fs.Config) (model.Model, error) {
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
-				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
 				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),
 				EOS:    int32(1),

model/models/gemma3/model_text.go

@@ -49,7 +49,7 @@ func newTextModel(c fs.Config) *TextModel {
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
-				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
 				EOS:    int32(c.Uint("tokenizer.ggml.eos_token_id")),
 			},

model/models/llama/model.go

@@ -41,7 +41,7 @@ func New(c fs.Config) (model.Model, error) {
 			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
-				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
 				Merges: c.Strings("tokenizer.ggml.merges"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
 				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),

model/models/mistral3/model_text.go

@@ -152,7 +152,7 @@ func NewTextModel(c fs.Config) (*TextModel, error) {
 			c.String("tokenizer.ggml.pretokenizer", `[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]*[\p{Ll}\p{Lm}\p{Lo}\p{M}]+|[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]+[\p{Ll}\p{Lm}\p{Lo}\p{M}]*|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n/]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
-				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
 				Merges: c.Strings("tokenizer.ggml.merges"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id", 1)),
 				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),

model/models/mllama/model.go

@@ -43,7 +43,7 @@ func New(c fs.Config) (model.Model, error) {
 			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
-				Types:  c.Uints("tokenizer.ggml.token_type"),
+				Types:  c.Ints("tokenizer.ggml.token_type"),
 				Merges: c.Strings("tokenizer.ggml.merges"),
 				BOS:    int32(c.Uint("tokenizer.ggml.bos_token_id")),
 				AddBOS: c.Bool("tokenizer.ggml.add_bos_token", true),

model/models/mllama/model_text.go

@@ -177,7 +177,7 @@ type TextDecoder struct {
 func (d *TextDecoder) Forward(ctx ml.Context, hiddenState, positionIDs, outputs, mask, crossAttentionStates, crossAttentionMask ml.Tensor, cache *kvcache.WrapperCache, opts *TextModelOptions) ml.Tensor {
 	for i, layer := range d.Layers {
 		layerType := selfAttentionLayer
-		if slices.Contains(opts.crossAttentionLayers, uint32(i)) {
+		if slices.Contains(opts.crossAttentionLayers, int32(i)) {
 			layerType = crossAttentionLayer
 		}
 
@@ -202,7 +202,7 @@ type TextModelOptions struct {
 	eps, ropeBase, ropeScale         float32
 	ropeDim                          uint32
 
-	crossAttentionLayers []uint32
+	crossAttentionLayers []int32
 }
 
 type TextModel struct {
@@ -225,7 +225,7 @@ func newTextModel(c fs.Config) *TextModel {
 	var decoderLayers []TextDecoderLayer
 	for i := range c.Uint("block_count") {
 		var textDecoderLayer TextDecoderLayer
-		if slices.Contains(c.Uints("attention.cross_attention_layers"), i) {
+		if slices.Contains(c.Ints("attention.cross_attention_layers"), int32(i)) {
 			textDecoderLayer = &TextCrossAttentionDecoderLayer{}
 		} else {
 			textDecoderLayer = &TextSelfAttentionDecoderLayer{}
@@ -244,7 +244,7 @@ func newTextModel(c fs.Config) *TextModel {
 			ropeBase:             c.Float("rope.freq_base"),
 			ropeScale:            c.Float("rope.freq_scale", 1),
 			ropeDim:              c.Uint("rope.dimension_count"),
-			crossAttentionLayers: c.Uints("attention.cross_attention_layers"),
+			crossAttentionLayers: c.Ints("attention.cross_attention_layers"),
 		},
 	}
 }

model/models/mllama/model_vision.go

@@ -96,10 +96,10 @@ type VisionEncoder struct {
 	Layers []VisionEncoderLayer
 }
 
-func (e *VisionEncoder) Forward(ctx ml.Context, hiddenState ml.Tensor, intermediateLayersIndices []uint32, opts *VisionModelOptions) (ml.Tensor, []ml.Tensor) {
+func (e *VisionEncoder) Forward(ctx ml.Context, hiddenState ml.Tensor, intermediateLayersIndices []int32, opts *VisionModelOptions) (ml.Tensor, []ml.Tensor) {
 	var intermediateHiddenStates []ml.Tensor
 	for i, layer := range e.Layers {
-		if slices.Contains(intermediateLayersIndices, uint32(i)) {
+		if slices.Contains(intermediateLayersIndices, int32(i)) {
 			intermediateHiddenStates = append(intermediateHiddenStates, hiddenState.Reshape(ctx, append([]int{1}, hiddenState.Shape()...)...))
 		}
 
@@ -154,7 +154,7 @@ type VisionModelOptions struct {
 	imageSize, patchSize           int
 	eps                            float32
 
-	intermediateLayersIndices []uint32
+	intermediateLayersIndices []int32
 }
 
 type VisionModel struct {
@@ -229,7 +229,7 @@ func newVisionModel(c fs.Config) *VisionModel {
 
 			eps: c.Float("vision.attention.layer_norm_epsilon"),
 
-			intermediateLayersIndices: c.Uints("vision.intermediate_layers_indices"),
+			intermediateLayersIndices: c.Ints("vision.intermediate_layers_indices"),
 		},
 	}
 }

model/process_text.go

@@ -37,7 +37,7 @@ type TextProcessor interface {
 
 type Vocabulary struct {
 	Values []string
-	Types  []uint32
+	Types  []int32
 	Scores []float32
 	Merges []string
 

model/process_text_spm_test.go

@@ -35,9 +35,9 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 			sentencepiece.ModelProto_SentencePiece_CONTROL,
 			sentencepiece.ModelProto_SentencePiece_UNUSED,
 			sentencepiece.ModelProto_SentencePiece_BYTE:
-			v.Types = append(v.Types, uint32(t))
+			v.Types = append(v.Types, int32(t))
 		default:
-			tt := uint32(sentencepiece.ModelProto_SentencePiece_NORMAL)
+			tt := int32(sentencepiece.ModelProto_SentencePiece_NORMAL)
 			// todo parse the special tokens file
 			//   - this will roundtrip correctly but the <start_of_turn> and
 			//     <end_of_turn> tokens aren't processed
@@ -124,7 +124,7 @@ func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
 			"<0xC3>",
 			"<0xA3>",
 		},
-		Types: []uint32{
+		Types: []int32{
 			TOKEN_TYPE_NORMAL,
 			TOKEN_TYPE_BYTE,
 			TOKEN_TYPE_BYTE,

model/process_text_test.go

@@ -28,7 +28,7 @@ func llama(t testing.TB) BytePairEncoding {
 		t.Fatal(err)
 	}
 
-	types := make([]uint32, len(vocab))
+	types := make([]int32, len(vocab))
 	tokens := make([]string, len(vocab))
 	for token, id := range vocab {
 		tokens[id] = token