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reenable LCM sampler
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ac43e0115c
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3 changed files with 8 additions and 4 deletions
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@ -982,7 +982,7 @@ Enter Prompt:<br>
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if friendlysdmodelname=="inactive" or fullsdmodelpath=="":
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response_body = (json.dumps([]).encode())
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else:
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response_body = (json.dumps([{"name":"Euler a","aliases":["k_euler_a","k_euler_ancestral"],"options":{}},{"name":"Euler","aliases":["k_euler"],"options":{}},{"name":"Heun","aliases":["k_heun"],"options":{}},{"name":"DPM2","aliases":["k_dpm_2"],"options":{}},{"name":"DPM++ 2M","aliases":["k_dpmpp_2m"],"options":{}}]).encode())
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response_body = (json.dumps([{"name":"Euler a","aliases":["k_euler_a","k_euler_ancestral"],"options":{}},{"name":"Euler","aliases":["k_euler"],"options":{}},{"name":"Heun","aliases":["k_heun"],"options":{}},{"name":"DPM2","aliases":["k_dpm_2"],"options":{}},{"name":"DPM++ 2M","aliases":["k_dpmpp_2m"],"options":{}},{"name":"LCM","aliases":["k_lcm"],"options":{}}]).encode())
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elif self.path.endswith('/sdapi/v1/latent-upscale-modes'):
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response_body = (json.dumps([]).encode())
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elif self.path.endswith('/sdapi/v1/upscalers'):
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@ -1756,7 +1756,7 @@ def show_new_gui():
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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.")
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quick_lowvram_box = makecheckbox(quick_tab, "Low VRAM", lowvram_var, 4,0,tooltiptxt="Low VRAM mode avoids offloading the KV cache to the GPU.")
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quick_lowvram_box = makecheckbox(quick_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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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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@ -1795,7 +1795,7 @@ def show_new_gui():
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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.")
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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", lowvram_var, 4,0, tooltiptxt='Select lowvram to not allocate VRAM scratch buffer/ "K" & "V" Cache.\nCan save a decent amount of VRAM, but makes fully offloaded model processing a bit slower.')
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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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