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feat(llama.cpp): support lora with scale and yarn (#1277)

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* 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 2023-11-11 18:40:48 +01:00 • committed by GitHub
parent bde87d00b9
commit 803a0ac02a
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GPG key ID: 4AEE18F83AFDEB23
13 changed files with 476 additions and 364 deletions
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1
api/backend/image.go
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@ -21,6 +21,7 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
PipelineType: c.Diffusers.PipelineType, PipelineType: c.Diffusers.PipelineType,
CFGScale: c.Diffusers.CFGScale, CFGScale: c.Diffusers.CFGScale,
LoraAdapter: c.LoraAdapter, LoraAdapter: c.LoraAdapter,
LoraScale: c.LoraScale,
LoraBase: c.LoraBase, LoraBase: c.LoraBase,
IMG2IMG: c.Diffusers.IMG2IMG, IMG2IMG: c.Diffusers.IMG2IMG,
CLIPModel: c.Diffusers.ClipModel, CLIPModel: c.Diffusers.ClipModel,

53
api/backend/options.go
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@ -38,30 +38,35 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
} }
return &pb.ModelOptions{ return &pb.ModelOptions{
ContextSize: int32(c.ContextSize), ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed), Seed: int32(c.Seed),
NBatch: int32(b), NBatch: int32(b),
NoMulMatQ: c.NoMulMatQ, NoMulMatQ: c.NoMulMatQ,
DraftModel: c.DraftModel, DraftModel: c.DraftModel,
AudioPath: c.VallE.AudioPath, AudioPath: c.VallE.AudioPath,
Quantization: c.Quantization, Quantization: c.Quantization,
MMProj: c.MMProj, MMProj: c.MMProj,
LoraAdapter: c.LoraAdapter, YarnExtFactor: c.YarnExtFactor,
LoraBase: c.LoraBase, YarnAttnFactor: c.YarnAttnFactor,
NGQA: c.NGQA, YarnBetaFast: c.YarnBetaFast,
RMSNormEps: c.RMSNormEps, YarnBetaSlow: c.YarnBetaSlow,
F16Memory: c.F16, LoraAdapter: c.LoraAdapter,
MLock: c.MMlock, LoraBase: c.LoraBase,
RopeFreqBase: c.RopeFreqBase, LoraScale: c.LoraScale,
RopeFreqScale: c.RopeFreqScale, NGQA: c.NGQA,
NUMA: c.NUMA, RMSNormEps: c.RMSNormEps,
Embeddings: c.Embeddings, F16Memory: c.F16,
LowVRAM: c.LowVRAM, MLock: c.MMlock,
NGPULayers: int32(c.NGPULayers), RopeFreqBase: c.RopeFreqBase,
MMap: c.MMap, RopeFreqScale: c.RopeFreqScale,
MainGPU: c.MainGPU, NUMA: c.NUMA,
Threads: int32(c.Threads), Embeddings: c.Embeddings,
TensorSplit: c.TensorSplit, LowVRAM: c.LowVRAM,
NGPULayers: int32(c.NGPULayers),
MMap: c.MMap,
MainGPU: c.MainGPU,
Threads: int32(c.Threads),
TensorSplit: c.TensorSplit,
// AutoGPTQ // AutoGPTQ
ModelBaseName: c.AutoGPTQ.ModelBaseName, ModelBaseName: c.AutoGPTQ.ModelBaseName,
Device: c.AutoGPTQ.Device, Device: c.AutoGPTQ.Device,

7
api/config/config.go
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@ -100,11 +100,18 @@ type LLMConfig struct {
NUMA bool `yaml:"numa"` NUMA bool `yaml:"numa"`
LoraAdapter string `yaml:"lora_adapter"` LoraAdapter string `yaml:"lora_adapter"`
LoraBase string `yaml:"lora_base"` LoraBase string `yaml:"lora_base"`
LoraScale float32 `yaml:"lora_scale"`
NoMulMatQ bool `yaml:"no_mulmatq"` NoMulMatQ bool `yaml:"no_mulmatq"`
DraftModel string `yaml:"draft_model"` DraftModel string `yaml:"draft_model"`
NDraft int32 `yaml:"n_draft"` NDraft int32 `yaml:"n_draft"`
Quantization string `yaml:"quantization"` Quantization string `yaml:"quantization"`
MMProj string `yaml:"mmproj"` MMProj string `yaml:"mmproj"`
RopeScaling string `yaml:"rope_scaling"`
YarnExtFactor float32 `yaml:"yarn_ext_factor"`
YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
YarnBetaFast float32 `yaml:"yarn_beta_fast"`
YarnBetaSlow float32 `yaml:"yarn_beta_slow"`
} }
type AutoGPTQ struct { type AutoGPTQ struct {

35
backend/cpp/llama/grpc-server.cpp
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@ -2017,12 +2017,41 @@ static void params_parse(const backend::ModelOptions* request,
if (!request->maingpu().empty()) { if (!request->maingpu().empty()) {
params.main_gpu = std::stoi(request->maingpu()); params.main_gpu = std::stoi(request->maingpu());
} }
// TODO: lora needs also a scale factor if (!request->loraadapter().empty() && !request->lorabase().empty()) {
//params.lora_adapter = request->loraadapter(); float scale_factor = 1.0f;
//params.lora_base = request->lorabase(); if (request->lorascale() != 0.0f) {
scale_factor = request->lorascale();
}
// get the directory of modelfile
std::string model_dir = params.model.substr(0, params.model.find_last_of("/\\"));
params.lora_adapter.push_back(std::make_tuple(model_dir + "/"+request->loraadapter(), scale_factor));
params.lora_base = model_dir + "/"+request->lorabase();
}
params.use_mlock = request->mlock(); params.use_mlock = request->mlock();
params.use_mmap = request->mmap(); params.use_mmap = request->mmap();
params.embedding = request->embeddings(); params.embedding = request->embeddings();
if (request->ropescaling() == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_NONE; }
else if (request->ropescaling() == "yarn") { params.rope_scaling_type = LLAMA_ROPE_SCALING_YARN; }
else { params.rope_scaling_type = LLAMA_ROPE_SCALING_LINEAR; }
if ( request->yarnextfactor() != 0.0f ) {
params.yarn_ext_factor = request->yarnextfactor();
}
if ( request->yarnattnfactor() != 0.0f ) {
params.yarn_attn_factor = request->yarnattnfactor();
}
if ( request->yarnbetafast() != 0.0f ) {
params.yarn_beta_fast = request->yarnbetafast();
}
if ( request->yarnbetaslow() != 0.0f ) {
params.yarn_beta_slow = request->yarnbetaslow();
}
if ( request->ropefreqbase() != 0.0f ) {
params.rope_freq_base = request->ropefreqbase();
}
if ( request->ropefreqscale() != 0.0f ) {
params.rope_freq_scale = request->ropefreqscale();
}
} }

56
extra/grpc/autogptq/backend_pb2.py
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extra/grpc/bark/backend_pb2.py
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extra/grpc/diffusers/backend_pb2.py
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extra/grpc/exllama/backend_pb2.py
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extra/grpc/huggingface/backend_pb2.py
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extra/grpc/vall-e-x/backend_pb2.py
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extra/grpc/vllm/backend_pb2.py
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344
pkg/grpc/proto/backend.pb.go
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@ -569,14 +569,20 @@ type ModelOptions struct {
// RWKV // RWKV
Tokenizer string `protobuf:"bytes,34,opt,name=Tokenizer,proto3" json:"Tokenizer,omitempty"` Tokenizer string `protobuf:"bytes,34,opt,name=Tokenizer,proto3" json:"Tokenizer,omitempty"`
// LLM (llama.cpp) // LLM (llama.cpp)
LoraBase string `protobuf:"bytes,35,opt,name=LoraBase,proto3" json:"LoraBase,omitempty"` LoraBase string `protobuf:"bytes,35,opt,name=LoraBase,proto3" json:"LoraBase,omitempty"`
LoraAdapter string `protobuf:"bytes,36,opt,name=LoraAdapter,proto3" json:"LoraAdapter,omitempty"` LoraAdapter string `protobuf:"bytes,36,opt,name=LoraAdapter,proto3" json:"LoraAdapter,omitempty"`
NoMulMatQ bool `protobuf:"varint,37,opt,name=NoMulMatQ,proto3" json:"NoMulMatQ,omitempty"` LoraScale float32 `protobuf:"fixed32,42,opt,name=LoraScale,proto3" json:"LoraScale,omitempty"`
DraftModel string `protobuf:"bytes,39,opt,name=DraftModel,proto3" json:"DraftModel,omitempty"` NoMulMatQ bool `protobuf:"varint,37,opt,name=NoMulMatQ,proto3" json:"NoMulMatQ,omitempty"`
AudioPath string `protobuf:"bytes,38,opt,name=AudioPath,proto3" json:"AudioPath,omitempty"` DraftModel string `protobuf:"bytes,39,opt,name=DraftModel,proto3" json:"DraftModel,omitempty"`
AudioPath string `protobuf:"bytes,38,opt,name=AudioPath,proto3" json:"AudioPath,omitempty"`
// vllm // vllm
Quantization string `protobuf:"bytes,40,opt,name=Quantization,proto3" json:"Quantization,omitempty"` Quantization string `protobuf:"bytes,40,opt,name=Quantization,proto3" json:"Quantization,omitempty"`
MMProj string `protobuf:"bytes,41,opt,name=MMProj,proto3" json:"MMProj,omitempty"` MMProj string `protobuf:"bytes,41,opt,name=MMProj,proto3" json:"MMProj,omitempty"`
RopeScaling string `protobuf:"bytes,43,opt,name=RopeScaling,proto3" json:"RopeScaling,omitempty"`
YarnExtFactor float32 `protobuf:"fixed32,44,opt,name=YarnExtFactor,proto3" json:"YarnExtFactor,omitempty"`
YarnAttnFactor float32 `protobuf:"fixed32,45,opt,name=YarnAttnFactor,proto3" json:"YarnAttnFactor,omitempty"`
YarnBetaFast float32 `protobuf:"fixed32,46,opt,name=YarnBetaFast,proto3" json:"YarnBetaFast,omitempty"`
YarnBetaSlow float32 `protobuf:"fixed32,47,opt,name=YarnBetaSlow,proto3" json:"YarnBetaSlow,omitempty"`
} }
func (x *ModelOptions) Reset() { func (x *ModelOptions) Reset() {
@ -863,6 +869,13 @@ func (x *ModelOptions) GetLoraAdapter() string {
return "" return ""
} }
func (x *ModelOptions) GetLoraScale() float32 {
if x != nil {
return x.LoraScale
}
return 0
}
func (x *ModelOptions) GetNoMulMatQ() bool { func (x *ModelOptions) GetNoMulMatQ() bool {
if x != nil { if x != nil {
return x.NoMulMatQ return x.NoMulMatQ
@ -898,6 +911,41 @@ func (x *ModelOptions) GetMMProj() string {
return "" return ""
} }
func (x *ModelOptions) GetRopeScaling() string {
if x != nil {
return x.RopeScaling
}
return ""
}
func (x *ModelOptions) GetYarnExtFactor() float32 {
if x != nil {
return x.YarnExtFactor
}
return 0
}
func (x *ModelOptions) GetYarnAttnFactor() float32 {
if x != nil {
return x.YarnAttnFactor
}
return 0
}
func (x *ModelOptions) GetYarnBetaFast() float32 {
if x != nil {
return x.YarnBetaFast
}
return 0
}
func (x *ModelOptions) GetYarnBetaSlow() float32 {
if x != nil {
return x.YarnBetaSlow
}
return 0
}
type Result struct { type Result struct {
state protoimpl.MessageState state protoimpl.MessageState
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
@ -1641,7 +1689,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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@ -1709,140 +1757,154 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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} }
var ( var (

8
pkg/grpc/proto/backend.proto
View file

@ -117,6 +117,8 @@ message ModelOptions {
// LLM (llama.cpp) // LLM (llama.cpp)
string LoraBase = 35; string LoraBase = 35;
string LoraAdapter = 36; string LoraAdapter = 36;
float LoraScale = 42;
bool NoMulMatQ = 37; bool NoMulMatQ = 37;
string DraftModel = 39; string DraftModel = 39;
@ -126,6 +128,12 @@ message ModelOptions {
string Quantization = 40; string Quantization = 40;
string MMProj = 41; string MMProj = 41;
string RopeScaling = 43;
float YarnExtFactor = 44;
float YarnAttnFactor = 45;
float YarnBetaFast = 46;
float YarnBetaSlow = 47;
} }
message Result { message Result {