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import gradio as gr |
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from utils import * |
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from transformers import pipeline |
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css = """ |
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""" |
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ori_model = None |
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edit_model = None |
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def slowly_reverse(word, progress=gr.Progress()): |
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progress(0, desc="Starting") |
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time.sleep(1) |
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progress(0.05) |
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new_string = "" |
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for letter in progress.tqdm(word, desc="Editing"): |
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time.sleep(0.25) |
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new_string = letter + new_string |
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return new_string |
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with gr.Blocks(css=css,theme=gr.themes.Soft(text_size="sm")) as demo: |
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with gr.Row(equal_height=True): |
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gr.HTML( |
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""" |
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<div style="display: flex; flex-direction: column; align-items: center;"> |
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<h1>🔧EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models</h1> |
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<p> |
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📑[<a href="https://huggingface.co/papers/2308.07269">Paper</a>] |
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👨💻[<a href="https://github.com/zjunlp/EasyEdit" target="_blank"><span class="icon"><i class="fab fa-github"></i></span>Code</a>] |
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📄[<a href="https://zjunlp.gitbook.io/easyedit">Docs</a>] |
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🤗[<a href="https://huggingface.co/spaces/zjunlp/EasyEdit" target="_blank">Demo</a>] |
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[<a href="https://arxiv.org/abs/2211.11031">via GRACE</a>] |
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</p> |
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</div> |
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""" |
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) |
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with gr.Row(): |
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gr.Markdown("#### Knowledge editing aims to subtly inject/edit updated knowledge or adjust undesirable behaviors, while minimizing the impact on unrelated inputs.") |
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with gr.Row(): |
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prompt = gr.Textbox(label="Edit Prompt") |
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target_new = gr.Textbox(label="Edit Target New") |
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with gr.Row(): |
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num_steps = gr.Slider(10, 100, value=40, step=1, label='Edit Steps') |
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replacement = gr.Dropdown( |
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choices=["replace_last", "replace_all", "replace_prompt"], |
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value="replace_last", |
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label="Replacement", |
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) |
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with gr.Row(): |
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button4clear = gr.Button("Clear") |
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button4edit = gr.Button("Edit",variant="primary") |
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with gr.Row(): |
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examples = gr.Examples( |
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examples=[ |
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["Who is the architect for Toodyay Fire Station?","Wong Tung & Sons"], |
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["Who is Claire Clairmont\'s sister?","Clairmont-Mayer"], |
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["Which fictional universe is Chlorophyll Kid part of?","Image Universe"] |
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], |
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examples_per_page=3, |
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inputs=[prompt,target_new], |
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) |
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with gr.Row(): |
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gr.HTML( |
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""" |
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<h3>Reliability Evaluation</h3> |
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""" |
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) |
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with gr.Row(): |
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input = gr.Textbox(label="Input Text") |
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with gr.Row(): |
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with gr.Column(): |
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button4gen_ori=gr.HighlightedText( |
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label="original output", |
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combine_adjacent=True, |
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show_legend=False, |
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color_map={"output": "yellow"}, |
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) |
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with gr.Column(): |
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button4gen_edit=gr.HighlightedText( |
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label="edited output", |
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combine_adjacent=True, |
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show_legend=False, |
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color_map={"output": "yellow"}, |
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) |
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with gr.Row(): |
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button4gen = gr.Button("Generate",variant="primary") |
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with gr.Row(): |
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gr.HTML( |
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""" |
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<h3>Locality Evaluation</h3> |
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""" |
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) |
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with gr.Row(): |
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loc_input = gr.Dropdown( |
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choices=[ |
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"who sang the theme song for laverne and shirley", |
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"when does the last episode of adventure time air", |
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"who plays alec ramsay in the black stallion", |
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"where did an independence movement occur because of the congress of vienna", |
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"where is the ucla usc game being played" |
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], |
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value="where is the ucla usc game being played", |
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label="Unrelated Input Text", |
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) |
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with gr.Row(): |
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with gr.Column(): |
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button4gen_loc_ori=gr.HighlightedText( |
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label="original output", |
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combine_adjacent=True, |
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show_legend=False, |
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color_map={"output": "green"}, |
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) |
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with gr.Column(): |
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button4gen_loc_edit=gr.HighlightedText( |
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label="edited output", |
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combine_adjacent=True, |
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show_legend=False, |
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color_map={"output": "green"}, |
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) |
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with gr.Row(): |
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button4locgen = gr.Button("Generate",variant="primary") |
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button4clear.click(lambda: ("", ""), outputs=[prompt,target_new]) |
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button4edit.click(fn=edit, inputs=[prompt,target_new, num_steps, replacement], outputs=input) |
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button4gen.click(fn=generate, inputs=[input, target_new], outputs=[button4gen_ori, button4gen_edit]) |
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button4locgen.click(fn=generate, inputs=loc_input, outputs=[button4gen_loc_ori, button4gen_loc_edit]) |
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with gr.Accordion("Citation", open=False): |
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gr.Markdown( |
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""" |
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```bibtex |
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@misc{wang2023easyedit, |
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title={EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models}, |
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author={Peng Wang and Ningyu Zhang and Xin Xie and Yunzhi Yao and Bozhong Tian and Mengru Wang and Zekun Xi and Siyuan Cheng and Kangwei Liu and Guozhou Zheng and Huajun Chen}, |
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year={2023}, |
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eprint={2308.07269}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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""" |
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) |
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demo.launch() |
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