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Update app.py
Browse files
app.py
CHANGED
@@ -41,8 +41,8 @@ def respond(
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llm = Llama(
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model_path=f"models/{model}",
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n_gpu_layers=0,
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n_batch=
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n_ctx=
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)
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llm_model = model
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@@ -107,7 +107,7 @@ demo = gr.ChatInterface(
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value="llama-3.2-1b-instruct-q4_k_m.gguf",
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label="Model"
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),
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gr.
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1. Complex reasoning and problem-solving
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2. Multilingual understanding and generation
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@@ -117,33 +117,20 @@ demo = gr.ChatInterface(
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6. Summarization and information extraction
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Always strive for accuracy, clarity, and helpfulness in your responses. If you're unsure about something, express your uncertainty. Use the following format for your responses:
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<thinking>
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[Your reasoning process here]
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</thinking>
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<output>
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[Your final response here]
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</output>
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If you need to correct yourself:
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<reflection>
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[Your correction and updated thoughts here]
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</reflection>""", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Max tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(
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minimum=0.1,
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maximum=2.0,
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value=0.
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step=0.05,
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label="Top-p",
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),
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gr.Slider(
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minimum=0,
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maximum=100,
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value=
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step=1,
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label="Top-k",
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),
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@@ -181,9 +168,7 @@ If you need to correct yourself:
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["Can you explain the concept of photosynthesis?"],
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["Write a short story about a robot learning to paint."],
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["Explain the difference between machine learning and deep learning."],
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["Can you help me debug this Python code?\n\ndef fibonacci(n):\n if n <= 0:\n return []\n elif n == 1:\n return [0]\n elif n == 2:\n return [0, 1]\n else:\n fib = [0, 1]\n for i in range(2, n):\n fib.append(fib[i-1] + fib[i-2])\n return fib\n\nprint(fibonacci(5))"],
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["Summarize the key points of climate change and its global impact."],
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["Translate this sentence to French, Spanish, and German: 'The quick brown fox jumps over the lazy dog.'"],
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["Explain quantum computing to a 10-year-old."],
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["Design a step-by-step meal plan for someone trying to lose weight and build muscle."]
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],
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llm = Llama(
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model_path=f"models/{model}",
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n_gpu_layers=0,
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n_batch=32000,
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n_ctx=2048,
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)
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llm_model = model
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value="llama-3.2-1b-instruct-q4_k_m.gguf",
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label="Model"
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),
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gr.TextArea(value="""You are Meta Llama 3.2 (1B), an advanced AI assistant created by Meta. Your capabilities include:
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1. Complex reasoning and problem-solving
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2. Multilingual understanding and generation
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6. Summarization and information extraction
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Always strive for accuracy, clarity, and helpfulness in your responses. If you're unsure about something, express your uncertainty. Use the following format for your responses:
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""", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Max tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(
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minimum=0.1,
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maximum=2.0,
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value=0.95,
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step=0.05,
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label="Top-p",
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),
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gr.Slider(
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minimum=0,
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maximum=100,
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value=40,
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step=1,
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label="Top-k",
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),
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["Can you explain the concept of photosynthesis?"],
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["Write a short story about a robot learning to paint."],
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["Explain the difference between machine learning and deep learning."],
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["Summarize the key points of climate change and its global impact."],
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["Explain quantum computing to a 10-year-old."],
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["Design a step-by-step meal plan for someone trying to lose weight and build muscle."]
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],
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