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Add settings UI for llama.cpp and fixed reloading of llama.cpp models (#2087)
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10869de0f4
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@ -16,6 +16,9 @@ class LlamaCppModel:
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def __init__(self):
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self.initialized = False
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def __del__(self):
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self.model.__del__()
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@classmethod
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def from_pretrained(self, path):
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result = self()
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@ -27,7 +27,7 @@ theme = gr.themes.Default(
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def list_model_elements():
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elements = ['cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'wbits', 'groupsize', 'model_type', 'pre_layer']
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elements = ['cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'wbits', 'groupsize', 'model_type', 'pre_layer', 'threads', 'n_batch', 'no-mmap', 'mlock', 'n_gpu_layers']
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for i in range(torch.cuda.device_count()):
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elements.append(f'gpu_memory_{i}')
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return elements
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15
server.py
15
server.py
@ -360,7 +360,20 @@ def create_model_menus():
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shared.gradio['download_model_button'] = gr.Button("Download")
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with gr.Column():
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shared.gradio['model_status'] = gr.Markdown('No model is loaded' if shared.model_name == 'None' else 'Ready')
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with gr.Box():
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gr.Markdown('llama.cpp parameters')
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with gr.Row():
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with gr.Column():
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shared.gradio['threads'] = gr.Slider(label="threads", minimum=0, step=1, maximum=32, value=shared.args.threads)
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shared.gradio['n_batch'] = gr.Slider(label="n_batch", minimum=1, maximum=2048, value=shared.args.n_batch)
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shared.gradio['n_gpu_layers'] = gr.Slider(label="n-gpu-layers", minimum=0, maximum=128, value=shared.args.n_gpu_layers)
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with gr.Column():
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shared.gradio['no-mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap)
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shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock)
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with gr.Row():
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shared.gradio['model_status'] = gr.Markdown('No model is loaded' if shared.model_name == 'None' else 'Ready')
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# In this event handler, the interface state is read and updated
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# with the model defaults (if any), and then the model is loaded
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