fix: Update model selection for the leaderboard

mteb/leaderboard/app.py

@@ -13,7 +13,6 @@
 import cachetools
 import gradio as gr
 import pandas as pd
-from gradio_rangeslider import RangeSlider
 
 import mteb
 from mteb.abstasks.TaskMetadata import TASK_DOMAIN, TASK_TYPE
@@ -158,10 +157,10 @@ def filter_models(
     availability: bool | None,
     compatibility: list[str],
     instructions: bool | None,
-    model_size: tuple[int | None, int | None],
+    max_model_size: int,
     zero_shot_setting: Literal["only_zero_shot", "allow_all", "remove_unknown"],
 ):
-    lower, upper = model_size
+    lower, upper = 0, max_model_size
     # Setting to None, when the user doesn't specify anything
     if (lower == MIN_MODEL_SIZE) or (lower is None):
         lower = None
@@ -179,6 +178,7 @@ def filter_models(
         frameworks=compatibility,
         n_parameters_range=(lower, upper),
     )
+
     models_to_keep = set()
     for model_meta in model_metas:
         is_model_zero_shot = model_meta.is_zero_shot_on(task_select)
@@ -217,7 +217,7 @@ def get_leaderboard_app() -> gr.Blocks:
         availability=None,
         compatibility=[],
         instructions=None,
-        model_size=(MIN_MODEL_SIZE, MAX_MODEL_SIZE),
+        max_model_size=MAX_MODEL_SIZE,
         zero_shot_setting="allow_all",
     )
 
@@ -378,11 +378,19 @@ def get_leaderboard_app() -> gr.Blocks:
                             label="Zero-shot",
                             interactive=True,
                         )
-                        model_size = RangeSlider(
-                            minimum=MIN_MODEL_SIZE,
-                            maximum=MAX_MODEL_SIZE,
-                            value=(MIN_MODEL_SIZE, MAX_MODEL_SIZE),
-                            label="Model Size (#M Parameters)",
+
+                        max_model_size = gr.Radio(
+                            [
+                                ("<100M", 100),
+                                ("<500M", 500),
+                                ("<1B", 1000),
+                                ("<5B", 5000),
+                                ("<10B", 10000),
+                                (">10B", MAX_MODEL_SIZE),
+                            ],
+                            value=MAX_MODEL_SIZE,
+                            label="Model Parameters",
+                            interactive=True,
                         )
 
         with gr.Tab("Summary"):
@@ -580,15 +588,15 @@ def update_task_list(
             availability,
             compatibility,
             instructions,
-            model_size,
+            max_model_size,
             zero_shot: hash(
                 (
                     id(scores),
                     hash(tuple(tasks)),
                     hash(availability),
                     hash(tuple(compatibility)),
                     hash(instructions),
-                    hash(model_size),
+                    hash(max_model_size),
                     hash(zero_shot),
                 )
             ),
@@ -599,7 +607,7 @@ def update_models(
             availability: bool | None,
             compatibility: list[str],
             instructions: bool | None,
-            model_size: tuple[int, int],
+            max_model_size: int,
             zero_shot: Literal["allow_all", "remove_unknown", "only_zero_shot"],
         ):
             start_time = time.time()
@@ -610,7 +618,7 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot_setting=zero_shot,
             )
             elapsed = time.time() - start_time
@@ -628,7 +636,7 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
@@ -641,7 +649,7 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
@@ -654,7 +662,7 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
@@ -667,7 +675,7 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
@@ -680,20 +688,20 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
         )
-        model_size.change(
+        max_model_size.change(
             update_models,
             inputs=[
                 scores,
                 task_select,
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
@@ -706,7 +714,7 @@ def update_models(
                 availability,
                 compatibility,
                 instructions,
-                model_size,
+                max_model_size,
                 zero_shot,
             ],
             outputs=[models],
@@ -784,7 +792,7 @@ def update_tables(
             availability=None,
             compatibility=[],
             instructions=None,
-            model_size=(MIN_MODEL_SIZE, MAX_MODEL_SIZE),
+            max_model_size=MAX_MODEL_SIZE,
             zero_shot="allow_all",
         )
         # We have to call this both on the filtered and unfiltered task because the callbacks

mteb/models/overview.py

@@ -79,8 +79,8 @@
     ru_sentence_models,
     salesforce_models,
     searchmap_models,
-    seed_models,
     seed_1_6_embedding_models,
+    seed_models,
     sentence_transformers_models,
     shuu_model,
     siglip_models,

mteb/models/seed_1_6_embedding_models.py

@@ -1,26 +1,26 @@
 from __future__ import annotations
 
-import os
+import base64
 import logging
+import os
 import time
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from functools import partial
+from io import BytesIO
 from typing import Any
 
-import base64
-from io import BytesIO
 import numpy as np
+import requests
 import torch
-from torch.utils.data import DataLoader
-from PIL import Image
 import tqdm
+from PIL import Image
+from torch.utils.data import DataLoader
 
 from mteb.encoder_interface import PromptType
 from mteb.model_meta import ModelMeta
 from mteb.models.bge_models import bge_chinese_training_data
 from mteb.models.wrapper import Wrapper
 from mteb.requires_package import requires_package
-import requests
-from concurrent.futures import ThreadPoolExecutor, as_completed
 
 logger = logging.getLogger(__name__)
 

pyproject.toml

@@ -72,7 +72,6 @@ speedtask = [
 peft = ["peft>=0.11.0"]
 leaderboard = [
     "gradio==5.27.1; python_version > '3.9'", # 3.10 is required for gradio
-    "gradio_rangeslider>=0.0.8",
     "plotly>=5.24.0,<6.0.0",
     "cachetools>=5.2.0",
     "matplotlib>=3.9.4",