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Detect CodeLlama settings
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@ -300,3 +300,7 @@ llama-65b-gptq-3bit:
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instruction_template: 'OpenOrca-Platypus2'
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custom_stopping_strings: '"### Instruction:", "### Response:"'
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rms_norm_eps: 5.0e-6
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.*codellama:
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rope_freq_base: 1000000
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.*codellama.*instruct:
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instruction_template: 'Llama-v2'
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@ -91,7 +91,7 @@ def create_ui():
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shared.gradio['gpu_split'] = gr.Textbox(label='gpu-split', info='Comma-separated list of VRAM (in GB) to use per GPU. Example: 20,7,7')
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shared.gradio['max_seq_len'] = gr.Slider(label='max_seq_len', minimum=0, maximum=16384, step=256, info='Maximum sequence length.', value=shared.args.max_seq_len)
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shared.gradio['alpha_value'] = gr.Slider(label='alpha_value', minimum=1, maximum=8, step=0.1, info='Positional embeddings alpha factor for NTK RoPE scaling. Use either this or compress_pos_emb, not both.', value=shared.args.alpha_value)
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shared.gradio['rope_freq_base'] = gr.Slider(label='rope_freq_base', minimum=0, maximum=100000, step=1000, info='If greater than 0, will be used instead of alpha_value. Those two are related by rope_freq_base = 10000 * alpha_value ^ (64 / 63)', value=shared.args.rope_freq_base)
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shared.gradio['rope_freq_base'] = gr.Slider(label='rope_freq_base', minimum=0, maximum=1000000, step=1000, info='If greater than 0, will be used instead of alpha_value. Those two are related by rope_freq_base = 10000 * alpha_value ^ (64 / 63)', value=shared.args.rope_freq_base)
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shared.gradio['compress_pos_emb'] = gr.Slider(label='compress_pos_emb', minimum=1, maximum=8, step=1, info='Positional embeddings compression factor. Should be set to (context length) / (model\'s original context length). Equal to 1/rope_freq_scale.', value=shared.args.compress_pos_emb)
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with gr.Column():
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