default rope params to 0 for new models (#968)

llm/llama.go

@@ -306,13 +306,19 @@ func newLlama(model string, adapters []string, runners []ModelRunner, numLayers
 	params := []string{
 		"--model", model,
 		"--ctx-size", fmt.Sprintf("%d", opts.NumCtx),
-		"--rope-freq-base", fmt.Sprintf("%f", opts.RopeFrequencyBase),
-		"--rope-freq-scale", fmt.Sprintf("%f", opts.RopeFrequencyScale),
 		"--batch-size", fmt.Sprintf("%d", opts.NumBatch),
 		"--n-gpu-layers", fmt.Sprintf("%d", numGPU),
 		"--embedding",
 	}
 
+	if opts.RopeFrequencyBase > 0 {
+		params = append(params, "--rope-freq-base", fmt.Sprintf("%f", opts.RopeFrequencyBase))
+	}
+
+	if opts.RopeFrequencyScale > 0 {
+		params = append(params, "--rope-freq-scale", fmt.Sprintf("%f", opts.RopeFrequencyScale))
+	}
+
 	if opts.NumGQA > 0 {
 		params = append(params, "--gqa", fmt.Sprintf("%d", opts.NumGQA))
 	}

llm/llm.go

@@ -85,7 +85,10 @@ func New(workDir, model string, adapters []string, opts api.Options) (LLM, error
 
 	switch ggml.Name() {
 	case "gguf":
-		opts.NumGQA = 0 // TODO: remove this when llama.cpp runners differ enough to need separate newLlama functions
+		// TODO: gguf will load these options automatically from the model binary
+		opts.NumGQA = 0
+		opts.RopeFrequencyBase = 0.0
+		opts.RopeFrequencyScale = 0.0
 		return newLlama(model, adapters, chooseRunners(workDir, "gguf"), ggml.NumLayers(), opts)
 	case "ggml", "ggmf", "ggjt", "ggla":
 		return newLlama(model, adapters, chooseRunners(workDir, "ggml"), ggml.NumLayers(), opts)