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import torch |
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from transformers import pipeline, logging, AutoModelForCausalLM, AutoTokenizer |
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import gradio as gr |
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model = AutoModelForCausalLM.from_pretrained( |
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"microsoft/phi-2", |
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torch_dtype=torch.float32, |
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device_map="cpu", |
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trust_remote_code=True |
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) |
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model.load_adapter('checkpoint-960') |
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tokenizer = AutoTokenizer.from_pretrained('checkpoint-960', trust_remote_code=True) |
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tokenizer.pad_token = tokenizer.eos_token |
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def generate_dialogue(input_text): |
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pipe = pipeline(task="text-generation",model=model,tokenizer=tokenizer,max_length=100) |
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result = pipe(f"<s>[INST] {input_text} [/INST]") |
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return result[0]['generated_text'] |
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HTML_TEMPLATE = """ |
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<style> |
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#app-header { |
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text-align: center; |
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background: rgba(255, 255, 255, 0.3); /* Semi-transparent white */ |
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padding: 20px; |
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border-radius: 10px; |
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); |
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position: relative; /* To position the artifacts */ |
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} |
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#app-header h1 { |
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color: #FF0000; |
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font-size: 2em; |
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margin-bottom: 10px; |
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} |
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.concept { |
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position: relative; |
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transition: transform 0.3s; |
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} |
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.concept:hover { |
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transform: scale(1.1); |
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} |
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.concept img { |
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width: 100px; |
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border-radius: 10px; |
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); |
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} |
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.concept-description { |
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position: absolute; |
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bottom: -30px; |
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left: 50%; |
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transform: translateX(-50%); |
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background-color: #4CAF50; |
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color: white; |
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padding: 5px 10px; |
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border-radius: 5px; |
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opacity: 0; |
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transition: opacity 0.3s; |
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} |
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.concept:hover .concept-description { |
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opacity: 1; |
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} |
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/* Artifacts */ |
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</style> |
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<div id="app-header"> |
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<!-- Artifacts --> |
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<div class="artifact large"></div> |
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<div class="artifact large"></div> |
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<div class="artifact large"></div> |
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<div class="artifact large"></div> |
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<!-- Content --> |
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<h1>Fine tuned Phi-2 Model LLM</h1> |
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<p>Generate dialogue for given context.</p> |
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<p>Model: Phi-2 (https://huggingface.co./microsoft/phi-2), Dataset: oasst1 (https://huggingface.co./datasets/OpenAssistant/oasst1) </p> |
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""" |
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with gr.Blocks(theme=gr.themes.Glass(),css=".gradio-container {background: url('https://github.com/nkanungo/S27/blob/main/bg.jpg?raw=true')}") as interface: |
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gr.HTML(value=HTML_TEMPLATE, show_label=False) |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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gr.Markdown("") |
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with gr.Row(): |
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input_text = gr.Textbox( |
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label="Input Text", |
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value="Enter your prompt here: This serves as the context for AI response." |
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) |
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outputs = gr.Textbox( |
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label="Response" |
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) |
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inputs = [input_text] |
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with gr.Column(): |
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button = gr.Button("Submit") |
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button.click(generate_dialogue, inputs=inputs, outputs=outputs) |
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interface.launch() |
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