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added desc and removed comments
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app.py
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@@ -114,7 +114,6 @@ additional_inputs=[
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def vote(data: gr.LikeData):
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if data.liked:
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print("You upvoted this response: " + data.value)
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@@ -124,10 +123,6 @@ def vote(data: gr.LikeData):
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chatbot = gr.Chatbot(avatar_images=('user.png', 'bot.png'),bubble_full_width = False)
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#chat = gr.ChatInterface(fn = random_response, chatbot = chatbot,
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# #chatbot = gr.Chatbot(avatar_images=('user.png', 'bot.png'),bubble_full_width = False),
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# textbox = gr.Textbox(placeholder="Ask me a yes or no question", container=False, scale=7),)
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chat_interface = gr.ChatInterface(
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generate,
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chatbot = chatbot,
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@@ -135,15 +130,6 @@ chat_interface = gr.ChatInterface(
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additional_inputs=additional_inputs,
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)
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#with gr.Blocks() as demo:
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# chatbot.like(vote, None, None)
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# chat.render()
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#additional_inputs = chatbot.like(vote, None, None))
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#chatbot.like(vote, None, None)
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#demo.like(vote, None, None)
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#demo.launch()
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with gr.Blocks() as demo:
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with gr.Row():
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gr.Image("better_banner.jpeg", elem_id="banner-image", show_label=False)
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with gr.Column():
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gr.Markdown(
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"""# Falcon-180B Demo
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**Chat with [Falcon-180B-Chat](https://huggingface.co/tiiuae/falcon-180b-chat), brainstorm ideas, discuss your holiday plans, and more!**
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✨ This demo is powered by [Falcon-180B](https://huggingface.co/tiiuae/falcon-180B) and finetuned on a mixture of [Ultrachat](https://huggingface.co/datasets/stingning/ultrachat), [Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus) and [Airoboros](https://huggingface.co/datasets/jondurbin/airoboros-2.1). [Falcon-180B](https://huggingface.co/tiiuae/falcon-180b) is a state-of-the-art large language model built by the [Technology Innovation Institute](https://www.tii.ae) in Abu Dhabi. It is trained on 3.5 trillion tokens (including [RefinedWeb](https://huggingface.co/datasets/tiiuae/falcon-refinedweb)) and available under the [Falcon-180B TII License](https://huggingface.co/spaces/tiiuae/falcon-180b-license/blob/main/LICENSE.txt). It currently holds the 🥇 1st place on the [🤗 Open LLM leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) for a pretrained model.
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chatbot.like(vote, None, None)
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chat_interface.render()
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#gr.ChatInterface(
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# generate,
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# examples=EXAMPLES,
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# additional_inputs=additional_inputs,
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# avatar_images = ('user.png', 'bot.png')
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#)
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demo.queue(concurrency_count=100, api_open=False).launch(show_api=False)
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]
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def vote(data: gr.LikeData):
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if data.liked:
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print("You upvoted this response: " + data.value)
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chatbot = gr.Chatbot(avatar_images=('user.png', 'bot.png'),bubble_full_width = False)
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chat_interface = gr.ChatInterface(
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generate,
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chatbot = chatbot,
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additional_inputs=additional_inputs,
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)
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with gr.Blocks() as demo:
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with gr.Row():
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gr.Image("better_banner.jpeg", elem_id="banner-image", show_label=False)
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with gr.Column():
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gr.Markdown(
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"""# Falcon-180B Demo
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## Gradio ChatInterface allows for dynamic Chat Bubble Sizing, User and Bot Avatars, and Like/Dislike buttons.
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**Chat with [Falcon-180B-Chat](https://huggingface.co/tiiuae/falcon-180b-chat), brainstorm ideas, discuss your holiday plans, and more!**
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✨ This demo is powered by [Falcon-180B](https://huggingface.co/tiiuae/falcon-180B) and finetuned on a mixture of [Ultrachat](https://huggingface.co/datasets/stingning/ultrachat), [Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus) and [Airoboros](https://huggingface.co/datasets/jondurbin/airoboros-2.1). [Falcon-180B](https://huggingface.co/tiiuae/falcon-180b) is a state-of-the-art large language model built by the [Technology Innovation Institute](https://www.tii.ae) in Abu Dhabi. It is trained on 3.5 trillion tokens (including [RefinedWeb](https://huggingface.co/datasets/tiiuae/falcon-refinedweb)) and available under the [Falcon-180B TII License](https://huggingface.co/spaces/tiiuae/falcon-180b-license/blob/main/LICENSE.txt). It currently holds the 🥇 1st place on the [🤗 Open LLM leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) for a pretrained model.
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chatbot.like(vote, None, None)
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chat_interface.render()
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demo.queue(concurrency_count=100, api_open=False).launch(show_api=False)
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