ollama/convert/convert_gemma2_adapter.go

92 lines
1.9 KiB
Go
Raw Normal View History

package convert
import (
"strings"
"github.com/pdevine/tensor"
"github.com/pdevine/tensor/native"
"github.com/ollama/ollama/llm"
)
type gemma2Adapter struct {
AdapterParameters
}
var _ AdapterConverter = (*gemma2Adapter)(nil)
func (p *gemma2Adapter) KV(baseKV llm.KV) llm.KV {
kv := p.AdapterParameters.KV()
kv["general.architecture"] = "gemma2"
return kv
}
func (p *gemma2Adapter) Tensors(ts []Tensor) []llm.Tensor {
var out []llm.Tensor
for _, t := range ts {
shape := t.Shape()
if (strings.HasSuffix(t.Name(), "weight.lora_a") && shape[0] > shape[1]) ||
(strings.HasSuffix(t.Name(), "weight.lora_b") && shape[0] < shape[1]) {
shape[0], shape[1] = shape[1], shape[0]
t.SetRepacker(p.repack)
}
out = append(out, llm.Tensor{
Name: t.Name(),
Kind: t.Kind(),
Shape: t.Shape(),
WriterTo: t,
})
}
return out
}
func (p *gemma2Adapter) Replacements() []string {
return []string{
"base_model.model.", "",
"model.layers", "blk",
"self_attn.q_proj", "attn_q",
"self_attn.k_proj", "attn_k",
"self_attn.v_proj", "attn_v",
"self_attn.o_proj", "attn_output",
"mlp.gate_proj", "ffn_gate",
"mlp.down_proj", "ffn_down",
"mlp.up_proj", "ffn_up",
"lora_A.weight", "weight.lora_a",
"lora_B.weight", "weight.lora_b",
"lora_a", "weight.lora_a",
"lora_b", "weight.lora_b",
}
}
func (p *gemma2Adapter) repack(name string, data []float32, shape []uint64) ([]float32, error) {
dims := []int{int(shape[1]), int(shape[0])}
n := tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
if err := n.T(1, 0); err != nil {
return nil, err
}
if err := n.Reshape(dims...); err != nil {
return nil, err
}
if err := n.Transpose(); err != nil {
return nil, err
}
ts, err := native.SelectF32(n, 1)
if err != nil {
return nil, err
}
var f32s []float32
for _, t := range ts {
f32s = append(f32s, t...)
}
return f32s, nil
}