ollama/llama/options.go

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2023-07-03 20:32:48 +00:00
// MIT License
// Copyright (c) 2023 go-skynet authors
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
package llama
type ModelOptions struct {
ContextSize int
Seed int
NBatch int
F16Memory bool
MLock bool
MMap bool
VocabOnly bool
LowVRAM bool
Embeddings bool
NUMA bool
NGPULayers int
MainGPU string
TensorSplit string
}
type PredictOptions struct {
Seed, Threads, Tokens, TopK, Repeat, Batch, NKeep int
TopP, Temperature, Penalty float64
F16KV bool
DebugMode bool
StopPrompts []string
IgnoreEOS bool
TailFreeSamplingZ float64
TypicalP float64
FrequencyPenalty float64
PresencePenalty float64
Mirostat int
MirostatETA float64
MirostatTAU float64
PenalizeNL bool
LogitBias string
TokenCallback func(string) bool
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MLock, MMap bool
MainGPU string
TensorSplit string
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}
type PredictOption func(p *PredictOptions)
type ModelOption func(p *ModelOptions)
var DefaultModelOptions ModelOptions = ModelOptions{
ContextSize: 512,
Seed: 0,
F16Memory: false,
MLock: false,
Embeddings: false,
MMap: true,
LowVRAM: false,
}
var DefaultOptions PredictOptions = PredictOptions{
Seed: -1,
Threads: 4,
Tokens: 128,
Penalty: 1.1,
Repeat: 64,
Batch: 512,
NKeep: 64,
TopK: 40,
TopP: 0.95,
TailFreeSamplingZ: 1.0,
TypicalP: 1.0,
Temperature: 0.8,
FrequencyPenalty: 0.0,
PresencePenalty: 0.0,
Mirostat: 0,
MirostatTAU: 5.0,
MirostatETA: 0.1,
MMap: true,
}
// SetContext sets the context size.
func SetContext(c int) ModelOption {
return func(p *ModelOptions) {
p.ContextSize = c
}
}
func SetModelSeed(c int) ModelOption {
return func(p *ModelOptions) {
p.Seed = c
}
}
// SetContext sets the context size.
func SetMMap(b bool) ModelOption {
return func(p *ModelOptions) {
p.MMap = b
}
}
// SetNBatch sets the n_Batch
func SetNBatch(n_batch int) ModelOption {
return func(p *ModelOptions) {
p.NBatch = n_batch
}
}
// Set sets the tensor split for the GPU
func SetTensorSplit(maingpu string) ModelOption {
return func(p *ModelOptions) {
p.TensorSplit = maingpu
}
}
// SetMainGPU sets the main_gpu
func SetMainGPU(maingpu string) ModelOption {
return func(p *ModelOptions) {
p.MainGPU = maingpu
}
}
// SetPredictionTensorSplit sets the tensor split for the GPU
func SetPredictionTensorSplit(maingpu string) PredictOption {
return func(p *PredictOptions) {
p.TensorSplit = maingpu
}
}
// SetPredictionMainGPU sets the main_gpu
func SetPredictionMainGPU(maingpu string) PredictOption {
return func(p *PredictOptions) {
p.MainGPU = maingpu
}
}
var VocabOnly ModelOption = func(p *ModelOptions) {
p.VocabOnly = true
}
var EnabelLowVRAM ModelOption = func(p *ModelOptions) {
p.LowVRAM = true
}
var EnableNUMA ModelOption = func(p *ModelOptions) {
p.NUMA = true
}
var EnableEmbeddings ModelOption = func(p *ModelOptions) {
p.Embeddings = true
}
var EnableF16Memory ModelOption = func(p *ModelOptions) {
p.F16Memory = true
}
var EnableF16KV PredictOption = func(p *PredictOptions) {
p.F16KV = true
}
var Debug PredictOption = func(p *PredictOptions) {
p.DebugMode = true
}
var EnableMLock ModelOption = func(p *ModelOptions) {
p.MLock = true
}
// Create a new PredictOptions object with the given options.
func NewModelOptions(opts ...ModelOption) ModelOptions {
p := DefaultModelOptions
for _, opt := range opts {
opt(&p)
}
return p
}
var IgnoreEOS PredictOption = func(p *PredictOptions) {
p.IgnoreEOS = true
}
// SetMlock sets the memory lock.
func SetMlock(b bool) PredictOption {
return func(p *PredictOptions) {
p.MLock = b
}
}
// SetMemoryMap sets memory mapping.
func SetMemoryMap(b bool) PredictOption {
return func(p *PredictOptions) {
p.MMap = b
}
}
// SetGPULayers sets the number of GPU layers to use to offload computation
func SetGPULayers(n int) ModelOption {
return func(p *ModelOptions) {
p.NGPULayers = n
}
}
// SetTokenCallback sets the prompts that will stop predictions.
func SetTokenCallback(fn func(string) bool) PredictOption {
return func(p *PredictOptions) {
p.TokenCallback = fn
}
}
// SetStopWords sets the prompts that will stop predictions.
func SetStopWords(stop ...string) PredictOption {
return func(p *PredictOptions) {
p.StopPrompts = stop
}
}
// SetSeed sets the random seed for sampling text generation.
func SetSeed(seed int) PredictOption {
return func(p *PredictOptions) {
p.Seed = seed
}
}
// SetThreads sets the number of threads to use for text generation.
func SetThreads(threads int) PredictOption {
return func(p *PredictOptions) {
p.Threads = threads
}
}
// SetTokens sets the number of tokens to generate.
func SetTokens(tokens int) PredictOption {
return func(p *PredictOptions) {
p.Tokens = tokens
}
}
// SetTopK sets the value for top-K sampling.
func SetTopK(topk int) PredictOption {
return func(p *PredictOptions) {
p.TopK = topk
}
}
// SetTopP sets the value for nucleus sampling.
func SetTopP(topp float64) PredictOption {
return func(p *PredictOptions) {
p.TopP = topp
}
}
// SetTemperature sets the temperature value for text generation.
func SetTemperature(temp float64) PredictOption {
return func(p *PredictOptions) {
p.Temperature = temp
}
}
// SetPenalty sets the repetition penalty for text generation.
func SetPenalty(penalty float64) PredictOption {
return func(p *PredictOptions) {
p.Penalty = penalty
}
}
// SetRepeat sets the number of times to repeat text generation.
func SetRepeat(repeat int) PredictOption {
return func(p *PredictOptions) {
p.Repeat = repeat
}
}
// SetBatch sets the batch size.
func SetBatch(size int) PredictOption {
return func(p *PredictOptions) {
p.Batch = size
}
}
// SetKeep sets the number of tokens from initial prompt to keep.
func SetNKeep(n int) PredictOption {
return func(p *PredictOptions) {
p.NKeep = n
}
}
// Create a new PredictOptions object with the given options.
func NewPredictOptions(opts ...PredictOption) PredictOptions {
p := DefaultOptions
for _, opt := range opts {
opt(&p)
}
return p
}
// SetTailFreeSamplingZ sets the tail free sampling, parameter z.
func SetTailFreeSamplingZ(tfz float64) PredictOption {
return func(p *PredictOptions) {
p.TailFreeSamplingZ = tfz
}
}
// SetTypicalP sets the typicality parameter, p_typical.
func SetTypicalP(tp float64) PredictOption {
return func(p *PredictOptions) {
p.TypicalP = tp
}
}
// SetFrequencyPenalty sets the frequency penalty parameter, freq_penalty.
func SetFrequencyPenalty(fp float64) PredictOption {
return func(p *PredictOptions) {
p.FrequencyPenalty = fp
}
}
// SetPresencePenalty sets the presence penalty parameter, presence_penalty.
func SetPresencePenalty(pp float64) PredictOption {
return func(p *PredictOptions) {
p.PresencePenalty = pp
}
}
// SetMirostat sets the mirostat parameter.
func SetMirostat(m int) PredictOption {
return func(p *PredictOptions) {
p.Mirostat = m
}
}
// SetMirostatETA sets the mirostat ETA parameter.
func SetMirostatETA(me float64) PredictOption {
return func(p *PredictOptions) {
p.MirostatETA = me
}
}
// SetMirostatTAU sets the mirostat TAU parameter.
func SetMirostatTAU(mt float64) PredictOption {
return func(p *PredictOptions) {
p.MirostatTAU = mt
}
}
// SetPenalizeNL sets whether to penalize newlines or not.
func SetPenalizeNL(pnl bool) PredictOption {
return func(p *PredictOptions) {
p.PenalizeNL = pnl
}
}
// SetLogitBias sets the logit bias parameter.
func SetLogitBias(lb string) PredictOption {
return func(p *PredictOptions) {
p.LogitBias = lb
}
}