74 lines
1.7 KiB
Go
74 lines
1.7 KiB
Go
package llm
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import (
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"fmt"
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"log"
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"os"
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"github.com/pbnjay/memory"
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"github.com/jmorganca/ollama/api"
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)
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type LLM interface {
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Predict([]int, string, func(api.GenerateResponse)) error
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Embedding(string) ([]float64, error)
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Encode(string) []int
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Decode(...int) string
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SetOptions(api.Options)
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Close()
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}
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func New(model string, adapters []string, opts api.Options) (LLM, error) {
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if _, err := os.Stat(model); err != nil {
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return nil, err
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}
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f, err := os.Open(model)
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if err != nil {
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return nil, err
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}
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defer f.Close()
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ggml, err := DecodeGGML(f, ModelFamilyLlama)
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if err != nil {
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return nil, err
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}
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switch ggml.FileType().String() {
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case "F32", "F16", "Q5_0", "Q5_1", "Q8_0":
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if opts.NumGPU != 0 {
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// F32, F16, Q5_0, Q5_1, and Q8_0 do not support Metal API and will
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// cause the runner to segmentation fault so disable GPU
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log.Printf("WARNING: GPU disabled for F32, F16, Q5_0, Q5_1, and Q8_0")
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opts.NumGPU = 0
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}
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}
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totalResidentMemory := memory.TotalMemory()
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switch ggml.ModelType() {
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case ModelType3B, ModelType7B:
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if totalResidentMemory < 8*1024*1024 {
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return nil, fmt.Errorf("model requires at least 8GB of memory")
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}
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case ModelType13B:
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if totalResidentMemory < 16*1024*1024 {
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return nil, fmt.Errorf("model requires at least 16GB of memory")
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}
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case ModelType30B:
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if totalResidentMemory < 32*1024*1024 {
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return nil, fmt.Errorf("model requires at least 32GB of memory")
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}
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case ModelType65B:
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if totalResidentMemory < 64*1024*1024 {
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return nil, fmt.Errorf("model requires at least 64GB of memory")
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}
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}
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switch ggml.ModelFamily() {
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case ModelFamilyLlama:
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return newLlama(model, adapters, opts)
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default:
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return nil, fmt.Errorf("unknown ggml type: %s", ggml.ModelFamily())
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}
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}
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