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Update app.py
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app.py
CHANGED
@@ -103,8 +103,6 @@ def bot(history, text_input, image, temperature, length_penalty, repetition_pena
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yield history + [["Please input image or wait for image to be uploaded before clicking submit.", None]]
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return
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chat_history = " ".join([item for sublist in history for item in sublist if item is not None]) # Flatten history
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if arnold_mode:
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system_prompt = """You are Arnold Schwarzenegger, the famous bodybuilder, actor, and former Mr. Olympia.
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Respond in his iconic style, using his catchphrases and focusing on fitness, bodybuilding, and motivation.
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@@ -112,7 +110,8 @@ def bot(history, text_input, image, temperature, length_penalty, repetition_pena
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else:
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system_prompt = "You are a helpful AI assistant. Provide clear and concise responses to the user's questions about the image and text input."
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response = infer(image, prompt, temperature, length_penalty, repetition_penalty, max_length, min_length, top_p)
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@@ -124,7 +123,7 @@ def bot(history, text_input, image, temperature, length_penalty, repetition_pena
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history[-1][1] = response[:i+1]
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time.sleep(0.05)
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yield history
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with gr.Blocks() as demo:
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gr.Markdown(DESCRIPTION)
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gr.Markdown("""## LLaVA, one of the greatest multimodal chat models is now available in Transformers with 4-bit quantization! ⚡️
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yield history + [["Please input image or wait for image to be uploaded before clicking submit.", None]]
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return
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if arnold_mode:
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system_prompt = """You are Arnold Schwarzenegger, the famous bodybuilder, actor, and former Mr. Olympia.
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Respond in his iconic style, using his catchphrases and focusing on fitness, bodybuilding, and motivation.
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else:
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system_prompt = "You are a helpful AI assistant. Provide clear and concise responses to the user's questions about the image and text input."
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# Use only the current input for generating the response
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prompt = f"{system_prompt}\nUSER: <image>\n{text_input}\nASSISTANT:"
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response = infer(image, prompt, temperature, length_penalty, repetition_penalty, max_length, min_length, top_p)
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history[-1][1] = response[:i+1]
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time.sleep(0.05)
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yield history
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+
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with gr.Blocks() as demo:
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gr.Markdown(DESCRIPTION)
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gr.Markdown("""## LLaVA, one of the greatest multimodal chat models is now available in Transformers with 4-bit quantization! ⚡️
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