convert

type AdapterConverter interface {
	// KV maps parameters to LLM key-values
	KV(ggml.KV) ggml.KV
	// Tensors maps input tensors to LLM tensors. Adapter specific modifications can be done here.
	Tensors([]Tensor) []*ggml.Tensor
	// Replacements returns a list of string pairs to replace in tensor names.
	// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
	Replacements() []string
}

type AdapterParameters struct {
	Alpha          uint32 `json:"lora_alpha"`
	LoraLayers     uint32 `json:"lora_layers"`
	LoraParameters struct {
		Rank  uint32  `json:"rank"`
		Alpha float32 `json:"alpha"`
		Scale float32 `json:"scale"`
	} `json:"lora_parameters"`
}

type ModelConverter interface {
	// KV maps parameters to LLM key-values
	KV(*Tokenizer) ggml.KV
	// Tensors maps input tensors to LLM tensors. Model specific modifications can be done here.
	Tensors([]Tensor) []*ggml.Tensor
	// Replacements returns a list of string pairs to replace in tensor names.
	// See [strings.Replacer](https://pkg.go.dev/strings#Replacer) for details
	Replacements() []string
	// contains filtered or unexported methods
}

type ModelParameters struct {
	Architectures []string `json:"architectures"`
	VocabSize     uint32   `json:"vocab_size"`

	TextModel struct {
		VocabSize uint32 `json:"vocab_size"`
	} `json:"text_config"`
}

type Repacker func(string, []float32, []uint64) ([]float32, error)

type SpecialVocabulary struct {
	Type     string
	ID       int
	Content  string
	AddToken bool

	// IDs is populated by generation_config.json
	IDs []int32
}

type Tensor interface {
	Name() string
	Shape() []uint64
	Kind() uint32
	SetRepacker(Repacker)
	WriteTo(io.Writer) (int64, error)
	Clone() Tensor
}

type Tokenizer struct {
	*Vocabulary
	SpecialVocabulary []*SpecialVocabulary
	Merges            []string

	Pre      string
	Template string
}

type Vocabulary struct {
	Model  string
	Tokens []string
	Scores []float32
	Types  []int32
}