go-mlx/internal/metal/model.go
2026-02-19 19:51:14 +00:00

73 lines
1.9 KiB
Go

//go:build darwin && arm64
package metal
import (
"encoding/json"
"fmt"
"os"
"path/filepath"
)
// InternalModel is the common interface for all transformer model architectures.
type InternalModel interface {
// Forward runs the model forward pass on token IDs with KV caches.
Forward(tokens *Array, caches []Cache) *Array
// NewCache creates per-layer KV caches for generation.
NewCache() []Cache
// NumLayers returns the number of transformer layers.
NumLayers() int
// Tokenizer returns the model's tokenizer.
Tokenizer() *Tokenizer
// ModelType returns the architecture identifier (e.g. "gemma3", "qwen3").
ModelType() string
// ApplyLoRA wraps target projection layers with LoRA adapters for training.
// Returns the adapter which holds references to all LoRA layers.
ApplyLoRA(cfg LoRAConfig) *LoRAAdapter
}
// QuantizationConfig holds quantization parameters from config.json.
type QuantizationConfig struct {
GroupSize int `json:"group_size"`
Bits int `json:"bits"`
}
// resolveWeight looks up a weight with optional "language_model." prefix.
func resolveWeight(weights map[string]*Array, name string) *Array {
if w, ok := weights[name]; ok {
return w
}
if w, ok := weights["language_model."+name]; ok {
return w
}
return nil
}
// loadModel auto-detects the model architecture from config.json and loads it.
func loadModel(modelPath string) (InternalModel, error) {
data, err := os.ReadFile(filepath.Join(modelPath, "config.json"))
if err != nil {
return nil, fmt.Errorf("model: load config: %w", err)
}
var probe struct {
ModelType string `json:"model_type"`
}
if err := json.Unmarshal(data, &probe); err != nil {
return nil, fmt.Errorf("model: parse model_type: %w", err)
}
switch probe.ModelType {
case "qwen3":
return LoadQwen3(modelPath)
case "gemma3", "gemma2":
return LoadGemma3(modelPath)
default:
return nil, fmt.Errorf("model: unsupported architecture %q", probe.ModelType)
}
}