update

app.py

@@ -177,72 +177,47 @@ with demo:
                 outputs=leaderboard_table
             )
     
-    with gr.Accordion("Submit a new model for evaluation"):
-        with gr.Row():
-            with gr.Column():
-                method_name_textbox = gr.Textbox(label="Method name")
-                #llama, phi
-                model_family_radio = gr.Radio(["llama", "phi"], value="llama", label="Model family")
-                forget_rate_radio = gr.Radio(["1%", "5%", "10%"], value="10%", label="Forget rate")
-                url_textbox = gr.Textbox(label="Url to model information")
-            with gr.Column():
-                organisation = gr.Textbox(label="Organisation")
-                mail = gr.Textbox(label="Contact email")
-                file_output = gr.File()
+    # with gr.Accordion("Submit a new model for evaluation"):
+    #     with gr.Row():
+    #         with gr.Column():
+    #             method_name_textbox = gr.Textbox(label="Method name")
+    #             #llama, phi
+    #             model_family_radio = gr.Radio(["llama", "phi"], value="llama", label="Model family")
+    #             forget_rate_radio = gr.Radio(["1%", "5%", "10%"], value="10%", label="Forget rate")
+    #             url_textbox = gr.Textbox(label="Url to model information")
+    #         with gr.Column():
+    #             organisation = gr.Textbox(label="Organisation")
+    #             mail = gr.Textbox(label="Contact email")
+    #             file_output = gr.File()
                 
 
 
-        submit_button = gr.Button("Submit Eval")
-        submission_result = gr.Markdown()
-        submit_button.click(
-            add_new_eval,
-            [
-                method_name_textbox,
-                model_family_radio,
-                forget_rate_radio,
-                url_textbox,
-                file_output,
-                organisation,
-                mail
-            ],
-            submission_result,
-        )
+    #     submit_button = gr.Button("Submit Eval")
+    #     submission_result = gr.Markdown()
+    #     submit_button.click(
+    #         add_new_eval,
+    #         [
+    #             method_name_textbox,
+    #             model_family_radio,
+    #             forget_rate_radio,
+    #             url_textbox,
+    #             file_output,
+    #             organisation,
+    #             mail
+    #         ],
+    #         submission_result,
+    #     )
 
 
 
 
     gr.Markdown("""
-    ## Quick Links
+    ## Links
 
-    - [**Website**](https://locuslab.github.io/tofu): The landing page for TOFU
-    - [**arXiv Paper**](http://arxiv.org/abs/2401.06121): Detailed information about the TOFU dataset and its significance in unlearning tasks.
-    - [**GitHub Repository**](https://github.com/locuslab/tofu): Access the source code, fine-tuning scripts, and additional resources for the TOFU dataset.
-    - [**Dataset on Hugging Face**](https://huggingface.co/datasets/locuslab/TOFU): Direct link to download the TOFU dataset.
-    - [**Leaderboard on Hugging Face Spaces**](https://huggingface.co/spaces/locuslab/tofu_leaderboard): Current rankings and submissions for the TOFU dataset challenges.
-    - [**Summary on Twitter**](https://x.com/_akhaliq/status/1745643293839327268): A concise summary and key takeaways from the project.
+    - [**Website**](https://cotaeval.github.io): The website for CoTaEval Project.
+    - [**GitHub Repository**](https://github.com/boyiwei/CoTaEval): For source code of evaluating the takedown methods with CoTaEval.
+    - [**Datasets**](https://huggingface.co/datasets/boyiwei/CoTaEval): Dataset for evaluation and unlearning.
 
-    ## Applicability 🚀
-
-    The dataset is in QA format, making it ideal for use with popular chat models such as Llama2, Mistral, or Qwen. However, it also works for any other large language model. The corresponding code base is written for the Llama2 model, but can be easily adapted to other models.
-    
-    ## Installation
-    
-    ```
-    conda create -n tofu python=3.10
-    conda activate tofu
-    conda install pytorch pytorch-cuda=11.8 -c pytorch -c nvidia
-    conda install -c "nvidia/label/cuda-11.8.0" cuda-toolkit
-    pip install -r requirements.txt
-    ```
-    
-    ## Loading the Dataset
-    
-    To load the dataset, use the following code:
-    
-    ```python
-    from datasets import load_dataset
-    dataset = load_dataset("locuslab/TOFU","full")
-    ```
 
 
     """)