Test editting

README.md

@@ -8,8 +8,6 @@ sdk_version: 4.4.0
 app_file: app.py
 pinned: true
 license: apache-2.0
-tags:
-  - leaderboard
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -239,92 +239,92 @@ with demo:
         with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=3):
             gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
         
-        # with gr.TabItem("🚀 Submit here! ", elem_id="llm-benchmark-tab-table", id=4):
-        #     with gr.Column():
-        #         with gr.Row():
-        #             gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
-
-        #         with gr.Column():
-        #             with gr.Accordion(
-        #                 f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
-        #                 open=False,
-        #             ):
-        #                 with gr.Row():
-        #                     finished_eval_table = gr.components.Dataframe(
-        #                         value=finished_eval_queue_df,
-        #                         headers=EVAL_COLS,
-        #                         datatype=EVAL_TYPES,
-        #                         row_count=5,
-        #                     )
-        #             with gr.Accordion(
-        #                 f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})",
-        #                 open=False,
-        #             ):
-        #                 with gr.Row():
-        #                     running_eval_table = gr.components.Dataframe(
-        #                         value=running_eval_queue_df,
-        #                         headers=EVAL_COLS,
-        #                         datatype=EVAL_TYPES,
-        #                         row_count=5,
-        #                     )
-
-        #             with gr.Accordion(
-        #                 f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
-        #                 open=False,
-        #             ):
-        #                 with gr.Row():
-        #                     pending_eval_table = gr.components.Dataframe(
-        #                         value=pending_eval_queue_df,
-        #                         headers=EVAL_COLS,
-        #                         datatype=EVAL_TYPES,
-        #                         row_count=5,
-        #                     )
-        #     with gr.Row():
-        #         gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
-
-        #     with gr.Row():
-        #         with gr.Column():
-        #             model_name_textbox = gr.Textbox(label="Model name")
-        #             revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
-        #             model_type = gr.Dropdown(
-        #                 choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
-        #                 label="Model type",
-        #                 multiselect=False,
-        #                 value=None,
-        #                 interactive=True,
-        #             )
-
-        #         with gr.Column():
-        #             precision = gr.Dropdown(
-        #                 choices=[i.value.name for i in Precision if i != Precision.Unknown],
-        #                 label="Precision",
-        #                 multiselect=False,
-        #                 value="float16",
-        #                 interactive=True,
-        #             )
-        #             weight_type = gr.Dropdown(
-        #                 choices=[i.value.name for i in WeightType],
-        #                 label="Weights type",
-        #                 multiselect=False,
-        #                 value="Original",
-        #                 interactive=True,
-        #             )
-        #             base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-
-        #     submit_button = gr.Button("Submit Eval")
-        #     submission_result = gr.Markdown()
-        #     submit_button.click(
-        #         add_new_eval,
-        #         [
-        #             model_name_textbox,
-        #             base_model_name_textbox,
-        #             revision_name_textbox,
-        #             precision,
-        #             weight_type,
-        #             model_type,
-        #         ],
-        #         submission_result,
-        #     )
+        with gr.TabItem("🚀 Submit here! ", elem_id="llm-benchmark-tab-table", id=4):
+            with gr.Column():
+                with gr.Row():
+                    gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
+
+                with gr.Column():
+                    with gr.Accordion(
+                        f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
+                        open=False,
+                    ):
+                        with gr.Row():
+                            finished_eval_table = gr.components.Dataframe(
+                                value=finished_eval_queue_df,
+                                headers=EVAL_COLS,
+                                datatype=EVAL_TYPES,
+                                row_count=5,
+                            )
+                    with gr.Accordion(
+                        f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})",
+                        open=False,
+                    ):
+                        with gr.Row():
+                            running_eval_table = gr.components.Dataframe(
+                                value=running_eval_queue_df,
+                                headers=EVAL_COLS,
+                                datatype=EVAL_TYPES,
+                                row_count=5,
+                            )
+
+                    with gr.Accordion(
+                        f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
+                        open=False,
+                    ):
+                        with gr.Row():
+                            pending_eval_table = gr.components.Dataframe(
+                                value=pending_eval_queue_df,
+                                headers=EVAL_COLS,
+                                datatype=EVAL_TYPES,
+                                row_count=5,
+                            )
+            with gr.Row():
+                gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
+
+            with gr.Row():
+                with gr.Column():
+                    model_name_textbox = gr.Textbox(label="Model name")
+                    revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
+                    model_type = gr.Dropdown(
+                        choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
+                        label="Model type",
+                        multiselect=False,
+                        value=None,
+                        interactive=True,
+                    )
+
+                with gr.Column():
+                    precision = gr.Dropdown(
+                        choices=[i.value.name for i in Precision if i != Precision.Unknown],
+                        label="Precision",
+                        multiselect=False,
+                        value="float16",
+                        interactive=True,
+                    )
+                    weight_type = gr.Dropdown(
+                        choices=[i.value.name for i in WeightType],
+                        label="Weights type",
+                        multiselect=False,
+                        value="Original",
+                        interactive=True,
+                    )
+                    base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
+
+            submit_button = gr.Button("Submit Eval")
+            submission_result = gr.Markdown()
+            submit_button.click(
+                add_new_eval,
+                [
+                    model_name_textbox,
+                    base_model_name_textbox,
+                    revision_name_textbox,
+                    precision,
+                    weight_type,
+                    model_type,
+                ],
+                submission_result,
+            )
 
     with gr.Row():
         with gr.Accordion("📙 Comment", open=False):

src/display/about.py

@@ -29,7 +29,7 @@ TITLE = """<h1 align="center" id="space-title">NPHardEval leaderboard</h1>"""
 INTRODUCTION_TEXT = """
 <div align="center">
     <img 
-        src="https://raw.githubusercontent.com/casmlab/NPHardEval/main/figure/NPHardEval_text_right.png"
+        src="https://raw.githubusercontent.com/casmlab/NPHardEval/main/NPHardEval_text_right.jpg"
         style="width: 80%;"
         alt="Selected problems and the Euler diagram of computational complexity classes"
     >

src/envs.py

@@ -5,7 +5,7 @@ from huggingface_hub import HfApi
 # clone / pull the lmeh eval data
 TOKEN = os.environ.get("TOKEN", None)
 
-OWNER = "NPHardEval"
+OWNER = "hyfrankl"
 REPO_ID = f"{OWNER}/NPHardEval-leaderboard"
 QUEUE_REPO = f"{OWNER}/NPHardEval-requests"
 RESULTS_REPO = f"{OWNER}/NPHardEval-results"