mirror of
https://github.com/likelovewant/ollama-for-amd.git
synced 2025-12-21 22:33:56 +00:00
multi-regexp pretokenizer (#12325)
This commit is contained in:
@@ -227,17 +227,6 @@ func New(c fs.Config) (model.Model, error) {
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m := Transformer{
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TransformerBlocks: make([]TransformerBlock, c.Uint("block_count")),
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BytePairEncoding: model.NewBytePairEncoding(
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c.String("tokenizer.ggml.pretokenizer",
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strings.Join([]string{
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`[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]*[\p{Ll}\p{Lm}\p{Lo}\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?`,
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`[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]+[\p{Ll}\p{Lm}\p{Lo}\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?`,
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`\p{N}{1,3}`,
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` ?[^\s\p{L}\p{N}]+[\r\n/]*`,
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`\s*[\r\n]+`,
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`\s+(?!\S)`,
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`\s+`,
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}, "|"),
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),
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -250,6 +239,15 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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strings.Join([]string{
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`[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]*[\p{Ll}\p{Lm}\p{Lo}\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?`,
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`[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]+[\p{Ll}\p{Lm}\p{Lo}\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?`,
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`\p{N}{1,3}`,
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` ?[^\s\p{L}\p{N}]+[\r\n/]*`,
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`\s*[\r\n]+`,
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`\s+(?!\S)`,
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`\s+`,
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}, "|"),
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),
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Options: Options{
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hiddenSize: int(c.Uint("embedding_length")),
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@@ -54,10 +54,30 @@ func New(c fs.Config) (model.Model, error) {
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}
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switch c.String("tokenizer.ggml.model") {
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case "gpt2":
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processor = model.NewBytePairEncoding(
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`(?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+`,
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&vocabulary,
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)
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var pretokenizers []string
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switch c.String("tokenizer.ggml.pre") {
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case "default":
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// no-op use the default bpe pretokenizer
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case "qwen2":
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pretokenizers = []string{
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"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
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}
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case "refact":
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pretokenizers = []string{
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`\p{N}`,
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`'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+`,
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}
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case "tekken":
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pretokenizers = []string{
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"[^\\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+",
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}
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default:
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// use a llama-style pretokenizer
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pretokenizers = []string{
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"(?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+",
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}
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}
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processor = model.NewBytePairEncoding(&vocabulary, pretokenizers...)
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case "llama":
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processor = model.NewSentencePiece(&vocabulary)
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default:
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@@ -34,8 +34,6 @@ func (p *Projector) Forward(ctx ml.Context, visionOutputs ml.Tensor) ml.Tensor {
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func New(c fs.Config) (model.Model, error) {
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m := Model{
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BytePairEncoding: model.NewBytePairEncoding(
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c.String("tokenizer.ggml.pretokenizer",
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`[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]*[\p{Ll}\p{Lm}\p{Lo}\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?|[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]+[\p{Ll}\p{Lm}\p{Lo}\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n/]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -48,6 +46,7 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]*[\p{Ll}\p{Lm}\p{Lo}\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?|[^\r\n\p{L}\p{N}]?[\p{Lu}\p{Lt}\p{Lm}\p{Lo}\p{M}]+[\p{Ll}\p{Lm}\p{Lo}\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n/]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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),
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ImageProcessor: newImageProcessor(c),
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VisionModel: newVisionModel(c),
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@@ -33,7 +33,6 @@ var _ model.TextProcessor = (*Model)(nil)
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func New(c fs.Config) (model.Model, error) {
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m := &Model{
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BytePairEncoding: model.NewBytePairEncoding(
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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+`),
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -46,6 +45,7 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`[^\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+`,
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),
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TextModel: newTextModel(c),
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VisionModel: newVisionModel(c),
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@@ -33,7 +33,6 @@ const (
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func New(c fs.Config) (model.Model, error) {
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m := Model{
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BytePairEncoding: model.NewBytePairEncoding(
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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+`),
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -46,6 +45,7 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`(?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+`,
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),
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ImageProcessor: newImageProcessor(c),
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VisionModel: newVisionModel(c),
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@@ -139,7 +139,6 @@ func New(c fs.Config) (model.Model, error) {
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m := Model{
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Layers: make([]DecoderLayer, c.Uint("block_count")),
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BytePairEncoding: model.NewBytePairEncoding(
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c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -152,6 +151,7 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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),
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Options: Options{
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hiddenSize: int(c.Uint("embedding_length")),
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@@ -29,7 +29,6 @@ var _ model.MultimodalProcessor = (*Model)(nil)
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func New(c fs.Config) (model.Model, error) {
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m := &Model{
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BytePairEncoding: model.NewBytePairEncoding(
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c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -42,6 +41,7 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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),
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TextModel: NewTextModel(c),
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VisionModel: newVisionModel(c),
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@@ -35,7 +35,6 @@ func newEmbed(c fs.Config) (model.Model, error) {
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}
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m := embedModel{
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BytePairEncoding: model.NewBytePairEncoding(
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`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -48,6 +47,7 @@ func newEmbed(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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),
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Model: &Model{
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Layers: layers,
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@@ -200,7 +200,6 @@ func New(c fs.Config) (model.Model, error) {
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m := Model{
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BytePairEncoding: model.NewBytePairEncoding(
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`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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&model.Vocabulary{
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Values: c.Strings("tokenizer.ggml.tokens"),
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Types: c.Ints("tokenizer.ggml.token_type"),
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@@ -213,6 +212,7 @@ func New(c fs.Config) (model.Model, error) {
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c.Ints("tokenizer.ggml.eos_token_ids")...,
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),
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},
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`(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`,
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),
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Layers: layers,
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Options: &Options{
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