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feat(llama.cpp): support lora with scale and yarn (#1277)
* feat(llama.cpp): support lora with scale Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(llama.cpp): support yarn Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
GitHub
parent
bde87d00b9
commit
803a0ac02a
@ -21,6 +21,7 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
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PipelineType: c.Diffusers.PipelineType,
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CFGScale: c.Diffusers.CFGScale,
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LoraAdapter: c.LoraAdapter,
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LoraScale: c.LoraScale,
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LoraBase: c.LoraBase,
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IMG2IMG: c.Diffusers.IMG2IMG,
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CLIPModel: c.Diffusers.ClipModel,
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@ -38,30 +38,35 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
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}
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return &pb.ModelOptions{
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ContextSize: int32(c.ContextSize),
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Seed: int32(c.Seed),
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NBatch: int32(b),
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NoMulMatQ: c.NoMulMatQ,
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DraftModel: c.DraftModel,
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AudioPath: c.VallE.AudioPath,
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Quantization: c.Quantization,
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MMProj: c.MMProj,
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LoraAdapter: c.LoraAdapter,
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LoraBase: c.LoraBase,
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NGQA: c.NGQA,
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RMSNormEps: c.RMSNormEps,
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F16Memory: c.F16,
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MLock: c.MMlock,
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RopeFreqBase: c.RopeFreqBase,
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RopeFreqScale: c.RopeFreqScale,
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NUMA: c.NUMA,
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Embeddings: c.Embeddings,
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LowVRAM: c.LowVRAM,
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NGPULayers: int32(c.NGPULayers),
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MMap: c.MMap,
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MainGPU: c.MainGPU,
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Threads: int32(c.Threads),
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TensorSplit: c.TensorSplit,
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ContextSize: int32(c.ContextSize),
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Seed: int32(c.Seed),
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NBatch: int32(b),
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NoMulMatQ: c.NoMulMatQ,
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DraftModel: c.DraftModel,
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AudioPath: c.VallE.AudioPath,
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Quantization: c.Quantization,
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MMProj: c.MMProj,
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YarnExtFactor: c.YarnExtFactor,
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YarnAttnFactor: c.YarnAttnFactor,
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YarnBetaFast: c.YarnBetaFast,
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YarnBetaSlow: c.YarnBetaSlow,
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LoraAdapter: c.LoraAdapter,
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LoraBase: c.LoraBase,
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LoraScale: c.LoraScale,
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NGQA: c.NGQA,
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RMSNormEps: c.RMSNormEps,
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F16Memory: c.F16,
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MLock: c.MMlock,
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RopeFreqBase: c.RopeFreqBase,
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RopeFreqScale: c.RopeFreqScale,
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NUMA: c.NUMA,
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Embeddings: c.Embeddings,
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LowVRAM: c.LowVRAM,
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NGPULayers: int32(c.NGPULayers),
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MMap: c.MMap,
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MainGPU: c.MainGPU,
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Threads: int32(c.Threads),
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TensorSplit: c.TensorSplit,
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// AutoGPTQ
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ModelBaseName: c.AutoGPTQ.ModelBaseName,
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Device: c.AutoGPTQ.Device,
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@ -100,11 +100,18 @@ type LLMConfig struct {
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NUMA bool `yaml:"numa"`
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LoraAdapter string `yaml:"lora_adapter"`
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LoraBase string `yaml:"lora_base"`
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LoraScale float32 `yaml:"lora_scale"`
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NoMulMatQ bool `yaml:"no_mulmatq"`
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DraftModel string `yaml:"draft_model"`
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NDraft int32 `yaml:"n_draft"`
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Quantization string `yaml:"quantization"`
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MMProj string `yaml:"mmproj"`
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RopeScaling string `yaml:"rope_scaling"`
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YarnExtFactor float32 `yaml:"yarn_ext_factor"`
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YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
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YarnBetaFast float32 `yaml:"yarn_beta_fast"`
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YarnBetaSlow float32 `yaml:"yarn_beta_slow"`
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}
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type AutoGPTQ struct {
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@ -2017,12 +2017,41 @@ static void params_parse(const backend::ModelOptions* request,
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if (!request->maingpu().empty()) {
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params.main_gpu = std::stoi(request->maingpu());
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}
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// TODO: lora needs also a scale factor
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//params.lora_adapter = request->loraadapter();
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//params.lora_base = request->lorabase();
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if (!request->loraadapter().empty() && !request->lorabase().empty()) {
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float scale_factor = 1.0f;
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if (request->lorascale() != 0.0f) {
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scale_factor = request->lorascale();
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}
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// get the directory of modelfile
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std::string model_dir = params.model.substr(0, params.model.find_last_of("/\\"));
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params.lora_adapter.push_back(std::make_tuple(model_dir + "/"+request->loraadapter(), scale_factor));
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params.lora_base = model_dir + "/"+request->lorabase();
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}
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params.use_mlock = request->mlock();
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params.use_mmap = request->mmap();
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params.embedding = request->embeddings();
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if (request->ropescaling() == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_NONE; }
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else if (request->ropescaling() == "yarn") { params.rope_scaling_type = LLAMA_ROPE_SCALING_YARN; }
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else { params.rope_scaling_type = LLAMA_ROPE_SCALING_LINEAR; }
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if ( request->yarnextfactor() != 0.0f ) {
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params.yarn_ext_factor = request->yarnextfactor();
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}
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if ( request->yarnattnfactor() != 0.0f ) {
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params.yarn_attn_factor = request->yarnattnfactor();
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}
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if ( request->yarnbetafast() != 0.0f ) {
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params.yarn_beta_fast = request->yarnbetafast();
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}
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if ( request->yarnbetaslow() != 0.0f ) {
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params.yarn_beta_slow = request->yarnbetaslow();
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}
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if ( request->ropefreqbase() != 0.0f ) {
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params.rope_freq_base = request->ropefreqbase();
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}
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if ( request->ropefreqscale() != 0.0f ) {
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params.rope_freq_scale = request->ropefreqscale();
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}
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}
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@ -569,14 +569,20 @@ type ModelOptions struct {
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// RWKV
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Tokenizer string `protobuf:"bytes,34,opt,name=Tokenizer,proto3" json:"Tokenizer,omitempty"`
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// LLM (llama.cpp)
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LoraBase string `protobuf:"bytes,35,opt,name=LoraBase,proto3" json:"LoraBase,omitempty"`
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LoraAdapter string `protobuf:"bytes,36,opt,name=LoraAdapter,proto3" json:"LoraAdapter,omitempty"`
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NoMulMatQ bool `protobuf:"varint,37,opt,name=NoMulMatQ,proto3" json:"NoMulMatQ,omitempty"`
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DraftModel string `protobuf:"bytes,39,opt,name=DraftModel,proto3" json:"DraftModel,omitempty"`
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AudioPath string `protobuf:"bytes,38,opt,name=AudioPath,proto3" json:"AudioPath,omitempty"`
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LoraBase string `protobuf:"bytes,35,opt,name=LoraBase,proto3" json:"LoraBase,omitempty"`
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LoraAdapter string `protobuf:"bytes,36,opt,name=LoraAdapter,proto3" json:"LoraAdapter,omitempty"`
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LoraScale float32 `protobuf:"fixed32,42,opt,name=LoraScale,proto3" json:"LoraScale,omitempty"`
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NoMulMatQ bool `protobuf:"varint,37,opt,name=NoMulMatQ,proto3" json:"NoMulMatQ,omitempty"`
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DraftModel string `protobuf:"bytes,39,opt,name=DraftModel,proto3" json:"DraftModel,omitempty"`
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AudioPath string `protobuf:"bytes,38,opt,name=AudioPath,proto3" json:"AudioPath,omitempty"`
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// vllm
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Quantization string `protobuf:"bytes,40,opt,name=Quantization,proto3" json:"Quantization,omitempty"`
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MMProj string `protobuf:"bytes,41,opt,name=MMProj,proto3" json:"MMProj,omitempty"`
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Quantization string `protobuf:"bytes,40,opt,name=Quantization,proto3" json:"Quantization,omitempty"`
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MMProj string `protobuf:"bytes,41,opt,name=MMProj,proto3" json:"MMProj,omitempty"`
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RopeScaling string `protobuf:"bytes,43,opt,name=RopeScaling,proto3" json:"RopeScaling,omitempty"`
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YarnExtFactor float32 `protobuf:"fixed32,44,opt,name=YarnExtFactor,proto3" json:"YarnExtFactor,omitempty"`
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YarnAttnFactor float32 `protobuf:"fixed32,45,opt,name=YarnAttnFactor,proto3" json:"YarnAttnFactor,omitempty"`
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YarnBetaFast float32 `protobuf:"fixed32,46,opt,name=YarnBetaFast,proto3" json:"YarnBetaFast,omitempty"`
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YarnBetaSlow float32 `protobuf:"fixed32,47,opt,name=YarnBetaSlow,proto3" json:"YarnBetaSlow,omitempty"`
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}
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func (x *ModelOptions) Reset() {
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@ -863,6 +869,13 @@ func (x *ModelOptions) GetLoraAdapter() string {
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return ""
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}
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func (x *ModelOptions) GetLoraScale() float32 {
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if x != nil {
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return x.LoraScale
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}
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return 0
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}
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func (x *ModelOptions) GetNoMulMatQ() bool {
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if x != nil {
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return x.NoMulMatQ
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@ -898,6 +911,41 @@ func (x *ModelOptions) GetMMProj() string {
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return ""
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}
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func (x *ModelOptions) GetRopeScaling() string {
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if x != nil {
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return x.RopeScaling
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}
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return ""
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}
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func (x *ModelOptions) GetYarnExtFactor() float32 {
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if x != nil {
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return x.YarnExtFactor
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}
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return 0
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}
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func (x *ModelOptions) GetYarnAttnFactor() float32 {
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if x != nil {
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return x.YarnAttnFactor
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}
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return 0
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}
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func (x *ModelOptions) GetYarnBetaFast() float32 {
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if x != nil {
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return x.YarnBetaFast
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}
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return 0
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}
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func (x *ModelOptions) GetYarnBetaSlow() float32 {
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if x != nil {
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return x.YarnBetaSlow
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}
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return 0
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}
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type Result struct {
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state protoimpl.MessageState
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sizeCache protoimpl.SizeCache
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@ -1641,7 +1689,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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}
|
||||
|
||||
var (
|
||||
|
||||
@ -117,6 +117,8 @@ message ModelOptions {
|
||||
// LLM (llama.cpp)
|
||||
string LoraBase = 35;
|
||||
string LoraAdapter = 36;
|
||||
float LoraScale = 42;
|
||||
|
||||
bool NoMulMatQ = 37;
|
||||
string DraftModel = 39;
|
||||
|
||||
@ -126,6 +128,12 @@ message ModelOptions {
|
||||
string Quantization = 40;
|
||||
|
||||
string MMProj = 41;
|
||||
|
||||
string RopeScaling = 43;
|
||||
float YarnExtFactor = 44;
|
||||
float YarnAttnFactor = 45;
|
||||
float YarnBetaFast = 46;
|
||||
float YarnBetaSlow = 47;
|
||||
}
|
||||
|
||||
message Result {
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user