mirror of
https://github.com/LostRuins/koboldcpp.git
synced 2026-05-09 19:46:11 +00:00
adjust some defaults and gui launcher
This commit is contained in:
Concedo
parent
06d9068c97
commit
3fdbe3351d
1 changed files with 65 additions and 51 deletions
116
koboldcpp.py
116
koboldcpp.py
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@ -726,13 +726,13 @@ fullsdmodelpath = "" #if empty, it's not initialized
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mmprojpath = "" #if empty, it's not initialized
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password = "" #if empty, no auth key required
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fullwhispermodelpath = "" #if empty, it's not initialized
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maxctx = 2048
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maxhordectx = 2048
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maxhordelen = 256
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maxctx = 4096
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maxhordectx = 4096
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maxhordelen = 350
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modelbusy = threading.Lock()
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requestsinqueue = 0
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defaultport = 5001
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KcppVersion = "1.69.1"
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KcppVersion = "1.70"
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showdebug = True
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showsamplerwarning = True
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showmaxctxwarning = True
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@ -781,7 +781,7 @@ def transform_genparams(genparams, api_format):
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genparams["use_default_badwordsids"] = genparams.get('ignore_eos', False)
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elif api_format==3 or api_format==4:
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genparams["max_length"] = genparams.get('max_tokens', (256 if api_format==4 else 150))
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genparams["max_length"] = genparams.get('max_tokens', (350 if api_format==4 else 150))
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presence_penalty = genparams.get('presence_penalty', genparams.get('frequency_penalty', 0.0))
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genparams["presence_penalty"] = presence_penalty
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# openai allows either a string or a list as a stop sequence
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@ -1733,6 +1733,13 @@ def show_new_gui():
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windowheight = max(256, min(1024, windowheight))
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root.geometry(str(windowwidth) + "x" + str(windowheight) + str(lastpos))
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ctk.set_widget_scaling(smallratio)
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changerunmode(1,1,1)
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togglerope(1,1,1)
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toggleflashattn(1,1,1)
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togglectxshift(1,1,1)
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togglehorde(1,1,1)
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togglesdquant(1,1,1)
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toggletaesd(1,1,1)
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if sys.platform=="darwin":
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root.resizable(False,False)
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@ -1912,36 +1919,39 @@ def show_new_gui():
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temp.bind("<Leave>", hide_tooltip)
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return temp
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def makelabel(parent, text, row, column=0, tooltiptxt=""):
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def makelabel(parent, text, row, column=0, tooltiptxt="", columnspan=1, padx=8):
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temp = ctk.CTkLabel(parent, text=text)
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temp.grid(row=row, column=column, padx=8, pady=1, stick="nw")
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temp.grid(row=row, column=column, padx=padx, pady=1, stick="nw", columnspan=columnspan)
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if tooltiptxt!="":
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temp.bind("<Enter>", lambda event: show_tooltip(event, tooltiptxt))
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temp.bind("<Leave>", hide_tooltip)
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return temp
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def makeslider(parent, label, options, var, from_ , to, row=0, width=160, height=10, set=0, tooltip=""):
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sliderLabel = makelabel(parent, options[set], row + 1, 1)
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sliderLabel = makelabel(parent, options[set], row + 1, 0, columnspan=2, padx=(width+12))
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titleLabel = makelabel(parent, label, row,0,tooltip)
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def sliderUpdate(a,b,c):
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sliderLabel.configure(text = options[int(var.get())])
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var.trace("w", sliderUpdate)
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slider = ctk.CTkSlider(parent, from_=from_, to=to, variable = var, width = width, height=height, border_width=5,number_of_steps=len(options) - 1)
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slider.grid(row=row+1, column=0, padx = 8, stick="w")
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slider.grid(row=row+1, column=0, padx = 8, stick="w", columnspan=2)
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slider.set(set)
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return slider, sliderLabel, titleLabel
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def makelabelentry(parent, text, var, row=0, width= 50,tooltip=""):
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def makelabelentry(parent, text, var, row=0, width=50, padx=8, singleline=False, tooltip=""):
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label = makelabel(parent, text, row,0,tooltip)
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entry = ctk.CTkEntry(parent, width=width, textvariable=var) #you cannot set placeholder text for SHARED variables
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entry.grid(row=row, column=1, padx= 8, stick="nw")
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if singleline:
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entry.grid(row=row, column=0, padx=padx, stick="nw")
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else:
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entry.grid(row=row, column=1, padx=padx, stick="nw")
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return entry, label
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def makefileentry(parent, text, searchtext, var, row=0, width=200, filetypes=[], onchoosefile=None, singlerow=False, tooltiptxt=""):
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label = makelabel(parent, text, row,0,tooltiptxt)
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def makefileentry(parent, text, searchtext, var, row=0, width=200, filetypes=[], onchoosefile=None, singlerow=False, singlecol=True, tooltiptxt=""):
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label = makelabel(parent, text, row,0,tooltiptxt,columnspan=3)
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def getfilename(var, text):
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initialDir = os.path.dirname(var.get())
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initialDir = initialDir if os.path.isdir(initialDir) else None
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@ -1954,10 +1964,14 @@ def show_new_gui():
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button = ctk.CTkButton(parent, 50, text="Browse", command= lambda a=var,b=searchtext:getfilename(a,b))
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if singlerow:
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entry.grid(row=row, column=1, padx=8, stick="w")
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button.grid(row=row, column=1, padx=144, stick="nw")
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button.grid(row=row, column=1, padx=(width+12), stick="nw")
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else:
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entry.grid(row=row+1, column=0, padx=8, stick="nw")
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button.grid(row=row+1, column=1, stick="nw")
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if singlecol:
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entry.grid(row=row+1, column=0, columnspan=3, padx=8, stick="nw")
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button.grid(row=row+1, column=0, columnspan=3, padx=(width+12), stick="nw")
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else:
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entry.grid(row=row+1, column=0, columnspan=1, padx=8, stick="nw")
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button.grid(row=row+1, column=1, columnspan=1, padx=8, stick="nw")
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return label, entry, button
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# decided to follow yellowrose's and kalomaze's suggestions, this function will automatically try to determine GPU identifiers
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@ -2251,7 +2265,7 @@ def show_new_gui():
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quick_gpuname_label = ctk.CTkLabel(quick_tab, text="")
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quick_gpuname_label.grid(row=3, column=1, padx=75, sticky="W")
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quick_gpuname_label.configure(text_color="#ffff00")
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quick_gpu_layers_entry,quick_gpu_layers_label = makelabelentry(quick_tab,"GPU Layers:", gpulayers_var, 6, 50,"How many layers to offload onto the GPU.\nVRAM intensive, usage increases with model and context size.\nRequires some trial and error to find the best fit value.\n\nCommon values for total layers, accuracy not guaranteed.\n\nLlama/Mistral 7b/8b: 33\nSolar 10.7b/11b: 49\nLlama 13b: 41\nLlama 20b(stack): 63\nLlama/Yi 34b: 61\nMixtral 8x7b: 33\nLlama 70b: 81")
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quick_gpu_layers_entry,quick_gpu_layers_label = makelabelentry(quick_tab,"GPU Layers:", gpulayers_var, 6, 50,tooltip="How many layers to offload onto the GPU.\nVRAM intensive, usage increases with model and context size.\nRequires some trial and error to find the best fit value.\n\nCommon values for total layers, accuracy not guaranteed.\n\nLlama/Mistral 7b/8b: 33\nSolar 10.7b/11b: 49\nLlama 13b: 41\nLlama 20b(stack): 63\nLlama/Yi 34b: 61\nMixtral 8x7b: 33\nLlama 70b: 81")
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quick_mmq_box = makecheckbox(quick_tab, "Use QuantMatMul (mmq)", mmq_var, 4,1,tooltiptxt="Enable MMQ mode instead of CuBLAS for prompt processing. Read the wiki. Speed may vary.")
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# quick boxes
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@ -2265,10 +2279,10 @@ def show_new_gui():
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for idx, name, in enumerate(quick_boxes):
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makecheckbox(quick_tab, name, quick_boxes[name], int(idx/2) +20, idx%2,tooltiptxt=quick_boxes_desc[name])
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# context size
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makeslider(quick_tab, "Context Size:", contextsize_text, context_var, 0, len(contextsize_text)-1, 30, set=3,tooltip="What is the maximum context size to support. Model specific. You cannot exceed it.\nLarger contexts require more memory, and not all models support it.")
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makeslider(quick_tab, "Context Size:", contextsize_text, context_var, 0, len(contextsize_text)-1, 30, width=280, set=5,tooltip="What is the maximum context size to support. Model specific. You cannot exceed it.\nLarger contexts require more memory, and not all models support it.")
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# load model
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makefileentry(quick_tab, "Model:", "Select GGML Model File", model_var, 40, 170, onchoosefile=on_picked_model_file,tooltiptxt="Select a GGUF or GGML model file on disk to be loaded.")
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makefileentry(quick_tab, "Model:", "Select GGML Model File", model_var, 40, 280, onchoosefile=on_picked_model_file,tooltiptxt="Select a GGUF or GGML model file on disk to be loaded.")
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# Hardware Tab
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hardware_tab = tabcontent["Hardware"]
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@ -2289,14 +2303,14 @@ def show_new_gui():
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gpuname_label = ctk.CTkLabel(hardware_tab, text="")
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gpuname_label.grid(row=3, column=1, padx=75, sticky="W")
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gpuname_label.configure(text_color="#ffff00")
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gpu_layers_entry,gpu_layers_label = makelabelentry(hardware_tab,"GPU Layers:", gpulayers_var, 6, 50,"How many layers to offload onto the GPU.\nVRAM intensive, usage increases with model and context size.\nRequires some trial and error to find the best fit value.\n\nCommon values for total layers, accuracy not guaranteed.\n\nLlama/Mistral 7b/8b: 33\nSolar 10.7b/11b: 49\nLlama 13b: 41\nLlama 20b(stack): 63\nLlama/Yi 34b: 61\nMixtral 8x7b: 33\nLlama 70b: 81")
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gpu_layers_entry,gpu_layers_label = makelabelentry(hardware_tab,"GPU Layers:", gpulayers_var, 6, 50,tooltip="How many layers to offload onto the GPU.\nVRAM intensive, usage increases with model and context size.\nRequires some trial and error to find the best fit value.\n\nCommon values for total layers, accuracy not guaranteed.\n\nLlama/Mistral 7b/8b: 33\nSolar 10.7b/11b: 49\nLlama 13b: 41\nLlama 20b(stack): 63\nLlama/Yi 34b: 61\nMixtral 8x7b: 33\nLlama 70b: 81")
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tensor_split_entry,tensor_split_label = makelabelentry(hardware_tab, "Tensor Split:", tensor_split_str_vars, 8, 80, tooltip='When using multiple GPUs this option controls how large tensors should be split across all GPUs.\nUses a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order.\nFor example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1.')
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lowvram_box = makecheckbox(hardware_tab, "Low VRAM (No KV offload)", lowvram_var, 4,0, tooltiptxt='Avoid offloading KV Cache or scratch buffers to VRAM.\nAllows more layers to fit, but may result in a speed loss.')
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mmq_box = makecheckbox(hardware_tab, "Use QuantMatMul (mmq)", mmq_var, 4,1, tooltiptxt="Enable MMQ mode to use finetuned kernels instead of default CuBLAS/HipBLAS for prompt processing.\nRead the wiki. Speed may vary.")
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splitmode_box = makecheckbox(hardware_tab, "Row-Split", rowsplit_var, 5,0, tooltiptxt="Split rows across GPUs instead of splitting layers and KV across GPUs.\nUses the main GPU for small tensors and intermediate results. Speed may vary.")
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# threads
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makelabelentry(hardware_tab, "Threads:" , threads_var, 11, 50,"How many threads to use.\nRecommended value is your CPU core count, defaults are usually OK.")
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makelabelentry(hardware_tab, "Threads:" , threads_var, 11, 50,tooltip="How many threads to use.\nRecommended value is your CPU core count, defaults are usually OK.")
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# hardware checkboxes
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hardware_boxes = {"Launch Browser": launchbrowser, "High Priority" : highpriority, "Disable MMAP":disablemmap, "Use mlock":usemlock, "Debug Mode":debugmode, "Keep Foreground":keepforeground}
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@ -2311,11 +2325,11 @@ def show_new_gui():
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makecheckbox(hardware_tab, name, hardware_boxes[name], int(idx/2) +30, idx%2, tooltiptxt=hardware_boxes_desc[name])
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# blas thread specifier
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makelabelentry(hardware_tab, "BLAS threads:" , blas_threads_var, 14, 50,"How many threads to use during BLAS processing.\nIf left blank, uses same value as regular thread count.")
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makelabelentry(hardware_tab, "BLAS threads:" , blas_threads_var, 14, 50,tooltip="How many threads to use during BLAS processing.\nIf left blank, uses same value as regular thread count.")
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# blas batch size
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makeslider(hardware_tab, "BLAS Batch Size:", blasbatchsize_text, blas_size_var, 0, 7, 16, set=5,tooltip="How many tokens to process at once per batch.\nLarger values use more memory.")
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makeslider(hardware_tab, "BLAS Batch Size:", blasbatchsize_text, blas_size_var, 0, 7, 16,width=200, set=5,tooltip="How many tokens to process at once per batch.\nLarger values use more memory.")
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# force version
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makelabelentry(hardware_tab, "Force Version:" , version_var, 100, 50,"If the autodetected version is wrong, you can change it here.\nLeave as 0 for default.")
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makelabelentry(hardware_tab, "Force Version:" , version_var, 100, 50,tooltip="If the autodetected version is wrong, you can change it here.\nLeave as 0 for default.")
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ctk.CTkButton(hardware_tab , text = "Run Benchmark", command = guibench ).grid(row=110,column=0, stick="se", padx= 0, pady=2)
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@ -2332,15 +2346,15 @@ def show_new_gui():
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# context size
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makeslider(tokens_tab, "Context Size:",contextsize_text, context_var, 0, len(contextsize_text)-1, 20, set=3,tooltip="What is the maximum context size to support. Model specific. You cannot exceed it.\nLarger contexts require more memory, and not all models support it.")
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makeslider(tokens_tab, "Context Size:",contextsize_text, context_var, 0, len(contextsize_text)-1, 20, width=280, set=5,tooltip="What is the maximum context size to support. Model specific. You cannot exceed it.\nLarger contexts require more memory, and not all models support it.")
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customrope_scale_entry, customrope_scale_label = makelabelentry(tokens_tab, "RoPE Scale:", customrope_scale,tooltip="For Linear RoPE scaling. RoPE frequency scale.")
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customrope_base_entry, customrope_base_label = makelabelentry(tokens_tab, "RoPE Base:", customrope_base,tooltip="For NTK Aware Scaling. RoPE frequency base.")
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customrope_scale_entry, customrope_scale_label = makelabelentry(tokens_tab, "RoPE Scale:", customrope_scale, row=23, padx=100, singleline=True, tooltip="For Linear RoPE scaling. RoPE frequency scale.")
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customrope_base_entry, customrope_base_label = makelabelentry(tokens_tab, "RoPE Base:", customrope_base, row=24, padx=100, singleline=True, tooltip="For NTK Aware Scaling. RoPE frequency base.")
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def togglerope(a,b,c):
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items = [customrope_scale_label, customrope_scale_entry,customrope_base_label, customrope_base_entry]
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for idx, item in enumerate(items):
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if customrope_var.get() == 1:
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item.grid(row=23 + int(idx/2), column=idx%2, padx=8, stick="nw")
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item.grid()
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else:
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item.grid_remove()
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makecheckbox(tokens_tab, "Custom RoPE Config", variable=customrope_var, row=22, command=togglerope,tooltiptxt="Override the default RoPE configuration with custom RoPE scaling.")
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@ -2348,14 +2362,14 @@ def show_new_gui():
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noqkvlabel = makelabel(tokens_tab,"Requirments Not Met",31,0,"Requires FlashAttention ENABLED and ContextShift DISABLED.")
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noqkvlabel.configure(text_color="#ff5555")
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qkvslider,qkvlabel,qkvtitle = makeslider(tokens_tab, "Quantize KV Cache:", quantkv_text, quantkv_var, 0, 2, 30, set=0,tooltip="Enable quantization of KV cache.\nRequires FlashAttention and disables ContextShift.")
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makefileentry(tokens_tab, "ChatCompletions Adapter:", "Select ChatCompletions Adapter File", chatcompletionsadapter_var, 32, filetypes=[("JSON Adapter", "*.json")], tooltiptxt="Select an optional ChatCompletions Adapter JSON file to force custom instruct tags.")
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makefileentry(tokens_tab, "ChatCompletions Adapter:", "Select ChatCompletions Adapter File", chatcompletionsadapter_var, 32, width=250, filetypes=[("JSON Adapter", "*.json")], tooltiptxt="Select an optional ChatCompletions Adapter JSON file to force custom instruct tags.")
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def pickpremadetemplate():
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initialDir = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'kcpp_adapters')
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initialDir = initialDir if os.path.isdir(initialDir) else None
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fnam = askopenfilename(title="Pick Premade ChatCompletions Adapter",filetypes=[("JSON Adapter", "*.json")], initialdir=initialDir)
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if fnam:
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chatcompletionsadapter_var.set(fnam)
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ctk.CTkButton(tokens_tab, 64, text="Pick Premade", command=pickpremadetemplate).grid(row=33, column=1, padx=62, stick="nw")
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ctk.CTkButton(tokens_tab, 64, text="Pick Premade", command=pickpremadetemplate).grid(row=33, column=0, padx=322, stick="nw")
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togglerope(1,1,1)
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toggleflashattn(1,1,1)
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togglectxshift(1,1,1)
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@ -2363,11 +2377,11 @@ def show_new_gui():
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# Model Tab
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model_tab = tabcontent["Model Files"]
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makefileentry(model_tab, "Model:", "Select GGML Model File", model_var, 1, onchoosefile=on_picked_model_file,tooltiptxt="Select a GGUF or GGML model file on disk to be loaded.")
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makefileentry(model_tab, "Lora:", "Select Lora File",lora_var, 3,tooltiptxt="Select an optional GGML LoRA adapter to use.\nLeave blank to skip.")
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makefileentry(model_tab, "Lora Base:", "Select Lora Base File", lora_base_var, 5,tooltiptxt="Select an optional F16 GGML LoRA base file to use.\nLeave blank to skip.")
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makefileentry(model_tab, "LLaVA mmproj:", "Select LLaVA mmproj File", mmproj_var, 7,tooltiptxt="Select a mmproj file to use for LLaVA.\nLeave blank to skip.")
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makefileentry(model_tab, "Preloaded Story:", "Select Preloaded Story File", preloadstory_var, 9,tooltiptxt="Select an optional KoboldAI JSON savefile \nto be served on launch to any client.")
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makefileentry(model_tab, "Model:", "Select GGML Model File", model_var, 1,width=280, onchoosefile=on_picked_model_file,tooltiptxt="Select a GGUF or GGML model file on disk to be loaded.")
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makefileentry(model_tab, "Lora:", "Select Lora File",lora_var, 3,width=280,tooltiptxt="Select an optional GGML LoRA adapter to use.\nLeave blank to skip.")
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makefileentry(model_tab, "Lora Base:", "Select Lora Base File", lora_base_var, 5,width=280,tooltiptxt="Select an optional F16 GGML LoRA base file to use.\nLeave blank to skip.")
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makefileentry(model_tab, "LLaVA mmproj:", "Select LLaVA mmproj File", mmproj_var, 7,width=280,tooltiptxt="Select a mmproj file to use for LLaVA.\nLeave blank to skip.")
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makefileentry(model_tab, "Preloaded Story:", "Select Preloaded Story File", preloadstory_var, 9,width=280,tooltiptxt="Select an optional KoboldAI JSON savefile \nto be served on launch to any client.")
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# Network Tab
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network_tab = tabcontent["Network"]
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@ -2381,19 +2395,19 @@ def show_new_gui():
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makecheckbox(network_tab, "Quiet Mode", quietmode, 4,tooltiptxt="Prevents all generation related terminal output from being displayed.")
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makecheckbox(network_tab, "NoCertify Mode (Insecure)", nocertifymode, 4, 1,tooltiptxt="Allows insecure SSL connections. Use this if you have cert errors and need to bypass certificate restrictions.")
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makefileentry(network_tab, "SSL Cert:", "Select SSL cert.pem file",ssl_cert_var, 5, width=130 ,filetypes=[("Unencrypted Certificate PEM", "*.pem")], singlerow=True,tooltiptxt="Select your unencrypted .pem SSL certificate file for https.\nCan be generated with OpenSSL.")
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makefileentry(network_tab, "SSL Key:", "Select SSL key.pem file", ssl_key_var, 7, width=130, filetypes=[("Unencrypted Key PEM", "*.pem")], singlerow=True,tooltiptxt="Select your unencrypted .pem SSL key file for https.\nCan be generated with OpenSSL.")
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makelabelentry(network_tab, "Password: ", password_var, 8, 150,tooltip="Enter a password required to use this instance.\nThis key will be required for all text endpoints.\nImage endpoints are not secured.")
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makefileentry(network_tab, "SSL Cert:", "Select SSL cert.pem file",ssl_cert_var, 5, width=200 ,filetypes=[("Unencrypted Certificate PEM", "*.pem")], singlerow=True,tooltiptxt="Select your unencrypted .pem SSL certificate file for https.\nCan be generated with OpenSSL.")
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makefileentry(network_tab, "SSL Key:", "Select SSL key.pem file", ssl_key_var, 7, width=200, filetypes=[("Unencrypted Key PEM", "*.pem")], singlerow=True,tooltiptxt="Select your unencrypted .pem SSL key file for https.\nCan be generated with OpenSSL.")
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makelabelentry(network_tab, "Password: ", password_var, 8, 200,tooltip="Enter a password required to use this instance.\nThis key will be required for all text endpoints.\nImage endpoints are not secured.")
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||||
|
||||
# Horde Tab
|
||||
horde_tab = tabcontent["Horde Worker"]
|
||||
makelabel(horde_tab, "Horde:", 18,0,"Settings for embedded AI Horde worker").grid(pady=10)
|
||||
|
||||
horde_name_entry, horde_name_label = makelabelentry(horde_tab, "Horde Model Name:", horde_name_var, 20, 180,"The model name to be displayed on the AI Horde.")
|
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horde_gen_entry, horde_gen_label = makelabelentry(horde_tab, "Gen. Length:", horde_gen_var, 21, 50,"The maximum amount to generate per request \nthat this worker will accept jobs for.")
|
||||
horde_context_entry, horde_context_label = makelabelentry(horde_tab, "Max Context:",horde_context_var, 22, 50,"The maximum context length \nthat this worker will accept jobs for.")
|
||||
horde_apikey_entry, horde_apikey_label = makelabelentry(horde_tab, "API Key (If Embedded Worker):",horde_apikey_var, 23, 180,"Your AI Horde API Key that you have registered.")
|
||||
horde_workername_entry, horde_workername_label = makelabelentry(horde_tab, "Horde Worker Name:",horde_workername_var, 24, 180,"Your worker's name to be displayed.")
|
||||
horde_name_entry, horde_name_label = makelabelentry(horde_tab, "Horde Model Name:", horde_name_var, 20, 180,tooltip="The model name to be displayed on the AI Horde.")
|
||||
horde_gen_entry, horde_gen_label = makelabelentry(horde_tab, "Gen. Length:", horde_gen_var, 21, 50,tooltip="The maximum amount to generate per request \nthat this worker will accept jobs for.")
|
||||
horde_context_entry, horde_context_label = makelabelentry(horde_tab, "Max Context:",horde_context_var, 22, 50,tooltip="The maximum context length \nthat this worker will accept jobs for.")
|
||||
horde_apikey_entry, horde_apikey_label = makelabelentry(horde_tab, "API Key (If Embedded Worker):",horde_apikey_var, 23, 180,tooltip="Your AI Horde API Key that you have registered.")
|
||||
horde_workername_entry, horde_workername_label = makelabelentry(horde_tab, "Horde Worker Name:",horde_workername_var, 24, 180,tooltip="Your worker's name to be displayed.")
|
||||
|
||||
def togglehorde(a,b,c):
|
||||
labels = [horde_name_label, horde_gen_label, horde_context_label, horde_apikey_label, horde_workername_label]
|
||||
|
|
@ -2414,12 +2428,12 @@ def show_new_gui():
|
|||
# Image Gen Tab
|
||||
|
||||
images_tab = tabcontent["Image Gen"]
|
||||
makefileentry(images_tab, "Stable Diffusion Model (safetensors/gguf):", "Select Stable Diffusion Model File", sd_model_var, 1, filetypes=[("*.safetensors *.gguf","*.safetensors *.gguf")], tooltiptxt="Select a .safetensors or .gguf Stable Diffusion model file on disk to be loaded.")
|
||||
makelabelentry(images_tab, "Clamped Mode (Limit Resolution)", sd_clamped_var, 4, 50,"Limit generation steps and resolution settings for shared use.\nSet to 0 to disable, otherwise value is the size limit (min 512px).")
|
||||
makelabelentry(images_tab, "Image Threads:" , sd_threads_var, 6, 50,"How many threads to use during image generation.\nIf left blank, uses same value as threads.")
|
||||
makefileentry(images_tab, "Stable Diffusion Model (safetensors/gguf):", "Select Stable Diffusion Model File", sd_model_var, 1, width=280, singlecol=False, filetypes=[("*.safetensors *.gguf","*.safetensors *.gguf")], tooltiptxt="Select a .safetensors or .gguf Stable Diffusion model file on disk to be loaded.")
|
||||
makelabelentry(images_tab, "Clamped Mode (Limit Resolution)", sd_clamped_var, 4, 50,tooltip="Limit generation steps and resolution settings for shared use.\nSet to 0 to disable, otherwise value is the size limit (min 512px).")
|
||||
makelabelentry(images_tab, "Image Threads:" , sd_threads_var, 6, 50,tooltip="How many threads to use during image generation.\nIf left blank, uses same value as threads.")
|
||||
|
||||
sdloritem1,sdloritem2,sdloritem3 = makefileentry(images_tab, "Image LoRA (Must be non-quant):", "Select SD lora file",sd_lora_var, 10 ,filetypes=[("*.safetensors *.gguf", "*.safetensors *.gguf")],tooltiptxt="Select a .safetensors or .gguf SD LoRA model file to be loaded.")
|
||||
sdloritem4,sdloritem5 = makelabelentry(images_tab, "Image LoRA Multiplier:" , sd_loramult_var, 12, 50,"What mutiplier value to apply the SD LoRA with.")
|
||||
sdloritem1,sdloritem2,sdloritem3 = makefileentry(images_tab, "Image LoRA (Must be non-quant):", "Select SD lora file",sd_lora_var, 10, width=280, singlecol=False, filetypes=[("*.safetensors *.gguf", "*.safetensors *.gguf")],tooltiptxt="Select a .safetensors or .gguf SD LoRA model file to be loaded.")
|
||||
sdloritem4,sdloritem5 = makelabelentry(images_tab, "Image LoRA Multiplier:" , sd_loramult_var, 12, 50,tooltip="What mutiplier value to apply the SD LoRA with.")
|
||||
def togglesdquant(a,b,c):
|
||||
if sd_quant_var.get()==1:
|
||||
sdloritem1.grid_remove()
|
||||
|
|
@ -2436,7 +2450,7 @@ def show_new_gui():
|
|||
makecheckbox(images_tab, "Compress Weights (Saves Memory)", sd_quant_var, 8,command=togglesdquant,tooltiptxt="Quantizes the SD model weights to save memory. May degrade quality.")
|
||||
|
||||
|
||||
sdvaeitem1,sdvaeitem2,sdvaeitem3 = makefileentry(images_tab, "Image VAE:", "Select SD VAE file",sd_vae_var, 14, filetypes=[("*.safetensors *.gguf", "*.safetensors *.gguf")],tooltiptxt="Select a .safetensors or .gguf SD VAE file to be loaded.")
|
||||
sdvaeitem1,sdvaeitem2,sdvaeitem3 = makefileentry(images_tab, "Image VAE:", "Select SD VAE file",sd_vae_var, 14, width=280, singlecol=False, filetypes=[("*.safetensors *.gguf", "*.safetensors *.gguf")],tooltiptxt="Select a .safetensors or .gguf SD VAE file to be loaded.")
|
||||
def toggletaesd(a,b,c):
|
||||
if sd_vaeauto_var.get()==1:
|
||||
sdvaeitem1.grid_remove()
|
||||
|
|
@ -2450,7 +2464,7 @@ def show_new_gui():
|
|||
|
||||
# audio tab
|
||||
audio_tab = tabcontent["Audio"]
|
||||
makefileentry(audio_tab, "Whisper Model:", "Select Whisper .bin Model File", whisper_model_var, 1, filetypes=[("*.bin","*.bin")], tooltiptxt="Select a Whisper .bin model file on disk to be loaded.")
|
||||
makefileentry(audio_tab, "Whisper Model:", "Select Whisper .bin Model File", whisper_model_var, 1, width=280, filetypes=[("*.bin","*.bin")], tooltiptxt="Select a Whisper .bin model file on disk to be loaded.")
|
||||
|
||||
# launch
|
||||
def guilaunch():
|
||||
|
|
@ -3719,7 +3733,7 @@ if __name__ == '__main__':
|
|||
compatgroup.add_argument("--usevulkan", help="Use Vulkan for GPU Acceleration. Can optionally specify GPU Device ID (e.g. --usevulkan 0).", metavar=('[Device ID]'), nargs='*', type=int, default=None)
|
||||
compatgroup.add_argument("--useclblast", help="Use CLBlast for GPU Acceleration. Must specify exactly 2 arguments, platform ID and device ID (e.g. --useclblast 1 0).", type=int, choices=range(0,9), nargs=2)
|
||||
compatgroup.add_argument("--noblas", help="Do not use any accelerated prompt ingestion", action='store_true')
|
||||
parser.add_argument("--contextsize", help="Controls the memory allocated for maximum context size, only change if you need more RAM for big contexts. (default 2048). Supported values are [256,512,1024,2048,3072,4096,6144,8192,12288,16384,24576,32768,49152,65536,98304,131072]. IF YOU USE ANYTHING ELSE YOU ARE ON YOUR OWN.",metavar=('[256,512,1024,2048,3072,4096,6144,8192,12288,16384,24576,32768,49152,65536,98304,131072]'), type=check_range(int,256,262144), default=2048)
|
||||
parser.add_argument("--contextsize", help="Controls the memory allocated for maximum context size, only change if you need more RAM for big contexts. (default 4096). Supported values are [256,512,1024,2048,3072,4096,6144,8192,12288,16384,24576,32768,49152,65536,98304,131072]. IF YOU USE ANYTHING ELSE YOU ARE ON YOUR OWN.",metavar=('[256,512,1024,2048,3072,4096,6144,8192,12288,16384,24576,32768,49152,65536,98304,131072]'), type=check_range(int,256,262144), default=4096)
|
||||
parser.add_argument("--gpulayers", help="Set number of layers to offload to GPU when using GPU. Requires GPU.",metavar=('[GPU layers]'), nargs='?', const=1, type=int, default=0)
|
||||
parser.add_argument("--tensor_split", help="For CUDA and Vulkan only, ratio to split tensors across multiple GPUs, space-separated list of proportions, e.g. 7 3", metavar=('[Ratios]'), type=float, nargs='+')
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue