docker-container-test

Dockerfile

@@ -49,6 +49,7 @@ WORKDIR /app
 
 # Environment variables
 ENV HF_HOME=/app/.cache \
+    TRANSFORMERS_CACHE=/app/.cache \
     HF_DATASETS_CACHE=/app/.cache \
     INTERNAL_API_PORT=7861 \
     PORT=7860 \

backend/README.md

@@ -70,7 +70,7 @@ The application uses several datasets on the HuggingFace Hub:
 - **Format**: Main dataset containing all scores and metrics
 - **Updates**: Automatic after model evaluations
 
-### 4. Official Providers Dataset (`{HF_ORGANIZATION}/official-providers`)
+### 4. Maintainers Highlight Dataset (`{HF_ORGANIZATION}/maintainers-highlight`)
 
 - **Operations**:
   - 📥 Read-only access for highlighted models
@@ -203,7 +203,7 @@ Swagger documentation available at http://localhost:7860/docs
         is_merged: boolean,
         is_moe: boolean,
         is_flagged: boolean,
-        is_official_provider: boolean
+        is_highlighted_by_maintainer: boolean
       },
       metadata: {
         upload_date: string,

backend/app/api/dependencies.py

@@ -2,7 +2,7 @@ from fastapi import Depends, HTTPException
 import logging
 from app.services.models import ModelService
 from app.services.votes import VoteService
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 

backend/app/api/endpoints/leaderboard.py

@@ -3,7 +3,7 @@ from typing import List, Dict, Any
 from app.services.leaderboard import LeaderboardService
 from app.core.fastapi_cache import cached, build_cache_key
 import logging
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 router = APIRouter()

backend/app/api/endpoints/models.py

@@ -4,7 +4,7 @@ import logging
 from app.services.models import ModelService
 from app.api.dependencies import get_model_service
 from app.core.fastapi_cache import cached
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 router = APIRouter(tags=["models"])

backend/app/api/endpoints/votes.py

@@ -3,7 +3,7 @@ from typing import Dict, Any, List
 from app.services.votes import VoteService
 from app.core.fastapi_cache import cached, build_cache_key, invalidate_cache_key
 import logging
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 router = APIRouter()

backend/app/asgi.py

@@ -12,7 +12,7 @@ import sys
 
 from app.api.router import router
 from app.core.fastapi_cache import setup_cache
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 from app.config import hf_config
 
 # Configure logging before anything else
@@ -99,7 +99,7 @@ async def startup_event():
     logger.info(LogFormatter.info(f"  - Queue: {hf_config.QUEUE_REPO}"))
     logger.info(LogFormatter.info(f"  - Aggregated: {hf_config.AGGREGATED_REPO}"))
     logger.info(LogFormatter.info(f"  - Votes: {hf_config.VOTES_REPO}"))
-    logger.info(LogFormatter.info(f"  - Official Providers: {hf_config.OFFICIAL_PROVIDERS_REPO}"))
+    logger.info(LogFormatter.info(f"  - Maintainers Highlight: {hf_config.MAINTAINERS_HIGHLIGHT_REPO}"))
     
     # Setup cache
     setup_cache()

backend/app/config/hf_config.py

@@ -1,9 +1,13 @@
+"""
+Hugging Face configuration module
+"""
 import os
 import logging
 from typing import Optional
 from huggingface_hub import HfApi
 from pathlib import Path
 from app.core.cache import cache_config
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 
@@ -22,7 +26,7 @@ API = HfApi(token=HF_TOKEN)
 QUEUE_REPO = f"{HF_ORGANIZATION}/requests"
 AGGREGATED_REPO = f"{HF_ORGANIZATION}/contents"
 VOTES_REPO = f"{HF_ORGANIZATION}/votes"
-OFFICIAL_PROVIDERS_REPO = f"{HF_ORGANIZATION}/official-providers"
+MAINTAINERS_HIGHLIGHT_REPO = f"{HF_ORGANIZATION}/maintainers-highlight"
 
 # File paths from cache config
 VOTES_PATH = cache_config.votes_file

backend/app/core/cache.py

@@ -3,7 +3,7 @@ import shutil
 from pathlib import Path
 from datetime import timedelta
 import logging
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 from app.config.base import (
     CACHE_ROOT,
     DATASETS_CACHE,
@@ -58,16 +58,16 @@ class CacheConfig:
     def _setup_environment(self):
         """Configure HuggingFace environment variables"""
         logger.info(LogFormatter.subsection("ENVIRONMENT SETUP"))
-
+        
         env_vars = {
             "HF_HOME": str(self.cache_root),
+            "TRANSFORMERS_CACHE": str(self.models_cache),
             "HF_DATASETS_CACHE": str(self.datasets_cache)
         }
-
+        
         for var, value in env_vars.items():
             os.environ[var] = value
             logger.info(LogFormatter.info(f"Set {var}={value}"))
-
         
     def get_cache_path(self, cache_type: str) -> Path:
         """Returns the path for a specific cache type"""

backend/app/core/fastapi_cache.py

@@ -4,7 +4,7 @@ from fastapi_cache.decorator import cache
 from datetime import timedelta
 from app.config import CACHE_TTL
 import logging
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 

backend/app/core/formatting.py

@@ -1,104 +0,0 @@
-import logging
-from typing import Dict, Any, List, Optional
-
-logger = logging.getLogger(__name__)
-
-class LogFormatter:
-    """Utility class for consistent log formatting across the application"""
-    
-    @staticmethod
-    def section(title: str) -> str:
-        """Create a section header"""
-        return f"\n{'='*20} {title.upper()} {'='*20}"
-    
-    @staticmethod
-    def subsection(title: str) -> str:
-        """Create a subsection header"""
-        return f"\n{'─'*20} {title} {'─'*20}"
-    
-    @staticmethod
-    def tree(items: Dict[str, Any], title: str = None) -> List[str]:
-        """Create a tree view of dictionary data"""
-        lines = []
-        if title:
-            lines.append(f"📊 {title}:")
-        
-        # Get the maximum length for alignment
-        max_key_length = max(len(str(k)) for k in items.keys())
-        
-        # Format each item
-        for i, (key, value) in enumerate(items.items()):
-            prefix = "└──" if i == len(items) - 1 else "├──"
-            if isinstance(value, (int, float)):
-                value = f"{value:,}"  # Add thousand separators
-            lines.append(f"{prefix} {str(key):<{max_key_length}}: {value}")
-        
-        return lines
-    
-    @staticmethod
-    def stats(stats: Dict[str, int], title: str = None) -> List[str]:
-        """Format statistics with icons"""
-        lines = []
-        if title:
-            lines.append(f"📊 {title}:")
-        
-        # Get the maximum length for alignment
-        max_key_length = max(len(str(k)) for k in stats.keys())
-        
-        # Format each stat with an appropriate icon
-        icons = {
-            "total": "📌",
-            "success": "✅",
-            "error": "❌",
-            "pending": "⏳",
-            "processing": "⚙️",
-            "finished": "✨",
-            "evaluating": "🔄",
-            "downloads": "⬇️",
-            "files": "📁",
-            "cached": "💾",
-            "size": "📏",
-            "time": "⏱️",
-            "rate": "🚀"
-        }
-        
-        # Format each item
-        for i, (key, value) in enumerate(stats.items()):
-            prefix = "└──" if i == len(stats) - 1 else "├──"
-            icon = icons.get(key.lower().split('_')[0], "•")
-            if isinstance(value, (int, float)):
-                value = f"{value:,}"  # Add thousand separators
-            lines.append(f"{prefix} {icon} {str(key):<{max_key_length}}: {value}")
-        
-        return lines
-    
-    @staticmethod
-    def progress_bar(current: int, total: int, width: int = 20) -> str:
-        """Create a progress bar"""
-        percentage = (current * 100) // total
-        filled = "█" * (percentage * width // 100)
-        empty = "░" * (width - len(filled))
-        return f"{filled}{empty} {percentage:3d}%"
-    
-    @staticmethod
-    def error(message: str, error: Optional[Exception] = None) -> str:
-        """Format error message"""
-        error_msg = f"\n❌ Error: {message}"
-        if error:
-            error_msg += f"\n   └── Details: {str(error)}"
-        return error_msg
-    
-    @staticmethod
-    def success(message: str) -> str:
-        """Format success message"""
-        return f"✅ {message}"
-    
-    @staticmethod
-    def warning(message: str) -> str:
-        """Format warning message"""
-        return f"⚠️  {message}"
-    
-    @staticmethod
-    def info(message: str) -> str:
-        """Format info message"""
-        return f"ℹ️  {message}"

backend/app/services/hf_service.py

@@ -2,7 +2,7 @@ from typing import Optional
 from huggingface_hub import HfApi
 from app.config import HF_TOKEN, API
 from app.core.cache import cache_config
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 import logging
 
 logger = logging.getLogger(__name__)

backend/app/services/leaderboard.py

@@ -5,7 +5,7 @@ import datasets
 from fastapi import HTTPException
 import logging
 from app.config.base import HF_ORGANIZATION
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 
@@ -143,7 +143,7 @@ class LeaderboardService:
                 "is_merged": data.get("Merged", False),
                 "is_moe": data.get("MoE", False),
                 "is_flagged": data.get("Flagged", False),
-                "is_official_provider": data.get("Official Providers", False)
+                "is_highlighted_by_maintainer": data.get("Official Providers", False)
             }
 
             metadata = {

backend/app/services/models.py

@@ -25,7 +25,7 @@ from app.services.hf_service import HuggingFaceService
 from app.utils.model_validation import ModelValidator
 from app.services.votes import VoteService
 from app.core.cache import cache_config
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 # Disable datasets progress bars globally
 disable_progress_bar()
@@ -409,14 +409,6 @@ class ModelService(HuggingFaceService):
             logger.info(LogFormatter.subsection("CHECKING EXISTING SUBMISSIONS"))
             existing_models = await self.get_models()
             
-            # Call the official provider status check
-            is_valid, error_message = await self.validator.check_official_provider_status(
-                model_data["model_id"],
-                existing_models
-            )
-            if not is_valid:
-                raise ValueError(error_message)
-
             # Check in all statuses (pending, evaluating, finished)
             for status, models in existing_models.items():
                 for model in models:
@@ -462,11 +454,11 @@ class ModelService(HuggingFaceService):
         if model_size is None:
             logger.error(LogFormatter.error("Model size validation failed", error))
             raise Exception(error)
-        logger.info(LogFormatter.success(f"Model size validation passed: {model_size:.1f}B"))
+        logger.info(LogFormatter.success(f"Model size validation passed: {model_size:.1f}GB"))
 
         # Size limits based on precision
         if model_data["precision"] in ["float16", "bfloat16"] and model_size > 100:
-            error_msg = f"Model too large for {model_data['precision']} (limit: 100B)"
+            error_msg = f"Model too large for {model_data['precision']} (limit: 100GB)"
             logger.error(LogFormatter.error("Size limit exceeded", error_msg))
             raise Exception(error_msg)
 

backend/app/services/votes.py

@@ -4,15 +4,16 @@ import json
 import logging
 import asyncio
 from pathlib import Path
+import os
 import aiohttp
 from huggingface_hub import HfApi
 import datasets
 
 from app.services.hf_service import HuggingFaceService
-from app.config import HF_TOKEN
+from app.config import HF_TOKEN, API
 from app.config.hf_config import HF_ORGANIZATION
 from app.core.cache import cache_config
-from app.core.formatting import LogFormatter
+from app.utils.logging import LogFormatter
 
 logger = logging.getLogger(__name__)
 

backend/app/utils/logging.py

@@ -1,3 +1,105 @@
-from app.core.formatting import LogFormatter
+import logging
+import sys
+from typing import Dict, Any, List, Optional
 
-__all__ = ['LogFormatter']
+logger = logging.getLogger(__name__)
+
+class LogFormatter:
+    """Utility class for consistent log formatting across the application"""
+    
+    @staticmethod
+    def section(title: str) -> str:
+        """Create a section header"""
+        return f"\n{'='*20} {title.upper()} {'='*20}"
+    
+    @staticmethod
+    def subsection(title: str) -> str:
+        """Create a subsection header"""
+        return f"\n{'─'*20} {title} {'─'*20}"
+    
+    @staticmethod
+    def tree(items: Dict[str, Any], title: str = None) -> List[str]:
+        """Create a tree view of dictionary data"""
+        lines = []
+        if title:
+            lines.append(f"📊 {title}:")
+        
+        # Get the maximum length for alignment
+        max_key_length = max(len(str(k)) for k in items.keys())
+        
+        # Format each item
+        for i, (key, value) in enumerate(items.items()):
+            prefix = "└──" if i == len(items) - 1 else "├──"
+            if isinstance(value, (int, float)):
+                value = f"{value:,}"  # Add thousand separators
+            lines.append(f"{prefix} {str(key):<{max_key_length}}: {value}")
+        
+        return lines
+    
+    @staticmethod
+    def stats(stats: Dict[str, int], title: str = None) -> List[str]:
+        """Format statistics with icons"""
+        lines = []
+        if title:
+            lines.append(f"📊 {title}:")
+        
+        # Get the maximum length for alignment
+        max_key_length = max(len(str(k)) for k in stats.keys())
+        
+        # Format each stat with an appropriate icon
+        icons = {
+            "total": "📌",
+            "success": "✅",
+            "error": "❌",
+            "pending": "⏳",
+            "processing": "⚙️",
+            "finished": "✨",
+            "evaluating": "🔄",
+            "downloads": "⬇️",
+            "files": "📁",
+            "cached": "💾",
+            "size": "📏",
+            "time": "⏱️",
+            "rate": "🚀"
+        }
+        
+        # Format each item
+        for i, (key, value) in enumerate(stats.items()):
+            prefix = "└──" if i == len(stats) - 1 else "├──"
+            icon = icons.get(key.lower().split('_')[0], "•")
+            if isinstance(value, (int, float)):
+                value = f"{value:,}"  # Add thousand separators
+            lines.append(f"{prefix} {icon} {str(key):<{max_key_length}}: {value}")
+        
+        return lines
+    
+    @staticmethod
+    def progress_bar(current: int, total: int, width: int = 20) -> str:
+        """Create a progress bar"""
+        percentage = (current * 100) // total
+        filled = "█" * (percentage * width // 100)
+        empty = "░" * (width - len(filled))
+        return f"{filled}{empty} {percentage:3d}%"
+    
+    @staticmethod
+    def error(message: str, error: Optional[Exception] = None) -> str:
+        """Format error message"""
+        error_msg = f"\n❌ Error: {message}"
+        if error:
+            error_msg += f"\n   └── Details: {str(error)}"
+        return error_msg
+    
+    @staticmethod
+    def success(message: str) -> str:
+        """Format success message"""
+        return f"✅ {message}"
+    
+    @staticmethod
+    def warning(message: str) -> str:
+        """Format warning message"""
+        return f"⚠️  {message}"
+    
+    @staticmethod
+    def info(message: str) -> str:
+        """Format info message"""
+        return f"ℹ️  {message}" 

backend/app/utils/model_validation.py

@@ -1,14 +1,15 @@
 import json
 import logging
 import asyncio
+import re
 from typing import Tuple, Optional, Dict, Any
-from datasets import load_dataset
+import aiohttp
 from huggingface_hub import HfApi, ModelCard, hf_hub_download
 from huggingface_hub import hf_api
 from transformers import AutoConfig, AutoTokenizer
-from app.config.base import HF_TOKEN
-from app.config.hf_config import OFFICIAL_PROVIDERS_REPO
-from app.core.formatting import LogFormatter
+from app.config.base import HF_TOKEN, API
+from app.utils.logging import LogFormatter
+
 
 logger = logging.getLogger(__name__)
 
@@ -104,12 +105,13 @@ class ModelValidator:
                 if adapter_meta and base_meta:
                     adapter_size = sum(adapter_meta.parameter_count.values())
                     base_size = sum(base_meta.parameter_count.values())
-                    model_size = adapter_size + base_size
+                    model_size = (adapter_size + base_size) / (2 * 1e9)  # Convert to billions, assuming float16
             else:
                 # For regular models, just get the model size
                 meta = await self.get_safetensors_metadata(model_info.id, revision=revision)
                 if meta:
-                    model_size = sum(meta.parameter_count.values()) # total params
+                    total_params = sum(meta.parameter_count.values())
+                    model_size = total_params / (2 * 1e9)  # Convert to billions, assuming float16
 
             if model_size is None:
                 # If model size could not be determined, return an error
@@ -117,7 +119,6 @@ class ModelValidator:
 
             # Adjust size for GPTQ models
             size_factor = 8 if (precision == "GPTQ" or "gptq" in model_info.id.lower()) else 1
-            model_size = model_size / 1e9  # Convert to billions, assuming float16
             model_size = round(size_factor * model_size, 3)
 
             logger.info(LogFormatter.success(f"Model size: {model_size}B parameters"))
@@ -206,61 +207,4 @@ class ModelValidator:
         except Exception as e:
             if "You are trying to access a gated repo." in str(e):
                 return True, "The model is gated and requires special access permissions.", None
-            return False, f"The model was not found or is misconfigured on the Hub. Error: {e.args[0]}", None
-
-    async def check_official_provider_status(
-        self, 
-        model_id: str,
-        existing_models: Dict[str, list]
-    ) -> Tuple[bool, Optional[str]]:
-        """
-        Check if model is from official provider and has finished submission.
-        
-        Args:
-            model_id: The model identifier (org/model-name)
-            existing_models: Dictionary of models by status from get_models()
-            
-        Returns:
-            Tuple[bool, Optional[str]]: (is_valid, error_message)
-        """
-        try:
-            logger.info(LogFormatter.info(f"Checking official provider status for {model_id}"))
-            
-            # Get model organization
-            model_org = model_id.split('/')[0] if '/' in model_id else None
-            
-            if not model_org:
-                return True, None
-                
-            # Load official providers dataset
-            dataset = load_dataset(OFFICIAL_PROVIDERS_REPO)
-            official_providers = dataset["train"][0]["CURATED_SET"]
-            
-            # Check if model org is in official providers
-            is_official = model_org in official_providers
-            
-            if is_official:
-                logger.info(LogFormatter.info(f"Model organization '{model_org}' is an official provider"))
-                
-                # Check for finished submissions
-                if "finished" in existing_models:
-                    for model in existing_models["finished"]:
-                        if model["name"] == model_id:
-                            error_msg = (
-                                f"Model {model_id} is an official provider model "
-                                f"with a completed evaluation. "
-                                f"To re-evaluate, please open a discussion."
-                            )
-                            logger.error(LogFormatter.error("Validation failed", error_msg))
-                            return False, error_msg
-                
-                logger.info(LogFormatter.success("No finished submission found for this official provider model"))
-            else:
-                logger.info(LogFormatter.info(f"Model organization '{model_org}' is not an official provider"))
-            
-            return True, None
-            
-        except Exception as e:
-            error_msg = f"Failed to check official provider status: {str(e)}"
-            logger.error(LogFormatter.error(error_msg))
-            return False, error_msg
+            return False, f"The model was not found or is misconfigured on the Hub. Error: {e.args[0]}", None

backend/pyproject.toml

@@ -13,8 +13,8 @@ pandas = "^2.2.3"
 datasets = "^3.2.0"
 pyarrow = "^18.1.0"
 python-multipart = "^0.0.20"
-huggingface-hub = "^0.27.1"
-transformers = "4.48.0"
+huggingface-hub = "^0.27.0"
+transformers = "^4.47.0"
 safetensors = "^0.4.5"
 aiofiles = "^24.1.0"
 fastapi-cache2 = "^0.2.1"

backend/utils/analyze_prod_datasets.py

@@ -132,7 +132,7 @@ def main():
                 "description": "User votes"
             },
             {
-                "id": f"{HF_ORGANIZATION}/official-providers",
+                "id": f"{HF_ORGANIZATION}/maintainers-highlight",
                 "description": "Highlighted models"
             }
         ]

backend/utils/fix_wrong_model_size.py

@@ -1,110 +0,0 @@
-import os
-import json
-import pytz
-import logging
-import asyncio
-from datetime import datetime
-from pathlib import Path
-import huggingface_hub
-from huggingface_hub.errors import RepositoryNotFoundError, RevisionNotFoundError
-from dotenv import load_dotenv
-from git import Repo
-from datetime import datetime
-from tqdm.auto import tqdm
-from tqdm.contrib.logging import logging_redirect_tqdm
-
-from app.config.hf_config import HF_TOKEN, API
-
-from app.utils.model_validation import ModelValidator
-
-huggingface_hub.logging.set_verbosity_error()
-huggingface_hub.utils.disable_progress_bars()
-
-logging.basicConfig(
-    level=logging.ERROR,
-    format='%(message)s'
-)
-logger = logging.getLogger(__name__)
-load_dotenv()
-
-validator = ModelValidator()
-
-def get_changed_files(repo_path, start_date, end_date):
-    repo = Repo(repo_path)
-    start = datetime.strptime(start_date, '%Y-%m-%d')
-    end = datetime.strptime(end_date, '%Y-%m-%d')
-    
-    changed_files = set()
-    pbar = tqdm(repo.iter_commits(), desc=f"Reading commits from {end_date} to {start_date}")
-    for commit in pbar:
-        commit_date = datetime.fromtimestamp(commit.committed_date)
-        pbar.set_postfix_str(f"Commit date: {commit_date}")
-        if start <= commit_date <= end:
-            changed_files.update(item.a_path for item in commit.diff(commit.parents[0]))
-
-        if commit_date < start:
-            break
-
-    return changed_files
-
-
-def read_json(repo_path, file):
-    with open(f"{repo_path}/{file}") as file:
-        return json.load(file)
-
-
-def write_json(repo_path, file, content):
-    with open(f"{repo_path}/{file}", "w") as file:
-        json.dump(content, file, indent=2)
-
-
-def main():
-    requests_path = "/requests"
-    start_date = "2024-12-09"
-    end_date = "2025-01-07"
-  
-    changed_files = get_changed_files(requests_path, start_date, end_date)
-
-    for file in tqdm(changed_files):
-        try:
-            request_data = read_json(requests_path, file)
-        except FileNotFoundError as e:
-            tqdm.write(f"File {file} not found")
-            continue
-    
-        try:
-            model_info = API.model_info(
-                repo_id=request_data["model"],
-                revision=request_data["revision"],
-                token=HF_TOKEN
-            )
-        except (RepositoryNotFoundError, RevisionNotFoundError) as e:
-            tqdm.write(f"Model info for {request_data["model"]} not found")
-            continue
-        
-        with logging_redirect_tqdm():
-            new_model_size, error = asyncio.run(validator.get_model_size(
-                model_info=model_info,
-                precision=request_data["precision"],
-                base_model=request_data["base_model"],
-                revision=request_data["revision"]
-            ))
-
-        if error:
-            tqdm.write(f"Error getting model size info for {request_data["model"]}, {error}")
-            continue
-        
-        old_model_size = request_data["params"]
-        if old_model_size != new_model_size:
-            if new_model_size > 100:
-                tqdm.write(f"Model: {request_data["model"]}, size is more 100B: {new_model_size}")
-            
-            tqdm.write(f"Model: {request_data["model"]}, old size: {request_data["params"]} new size: {new_model_size}")
-            tqdm.write(f"Updating request file {file}")
-
-            request_data["params"] = new_model_size
-            write_json(requests_path, file, content=request_data)
-
-
-if __name__ == "__main__":
-    main()

backend/utils/sync_datasets_locally.py

@@ -30,7 +30,7 @@ DATASET_NAMES = [
     "results",
     "requests",
     "contents",
-    "official-providers",
+    "maintainers-highlight",
 ]
 
 # Build list of datasets with their source and destination paths

frontend/src/pages/AddModelPage/components/ModelSubmissionForm/ModelSubmissionForm.js

@@ -411,7 +411,7 @@ function ModelSubmissionForm({ user, isAuthenticated }) {
                   placeholder="organization/model-name"
                   value={formData.modelName}
                   onChange={handleChange}
-                  helperText="Example: meta-llama/Llama-3.2-1B"
+                  helperText="Example: meta-llama/Llama-2-7b-hf"
                   InputProps={{
                     endAdornment: (
                       <InfoIconWithTooltip tooltip={HELP_TEXTS.modelName} />

frontend/src/pages/LeaderboardPage/components/Leaderboard/components/Filters/FilteredModelCount.js

@@ -19,7 +19,7 @@ const useModelCount = ({ totalCount, filteredCount, data, table, loading }) => {
       };
     }
     const displayCount = isOfficialProviderActive
-      ? officialOnlyCounts.officialProviders
+      ? officialOnlyCounts.maintainersHighlight
       : totalCount;
 
     // Calculate total number of pinned models
@@ -46,8 +46,8 @@ const useModelCount = ({ totalCount, filteredCount, data, table, loading }) => {
         // Filter by official providers
         if (filterConfig.isOfficialProviderActive) {
           if (
-            !model.features?.is_official_provider &&
-            !model.metadata?.is_official_provider
+            !model.features?.is_highlighted_by_maintainer &&
+            !model.metadata?.is_highlighted_by_maintainer
           ) {
             return false;
           }
@@ -100,7 +100,7 @@ const useModelCount = ({ totalCount, filteredCount, data, table, loading }) => {
                 typeof filter === "object" ? filter.value : filter;
 
               // Maintainer's Highlight keeps positive logic
-              if (filterValue === "is_official_provider") {
+              if (filterValue === "is_highlighted_by_maintainer") {
                 return model.features[filterValue];
               }
 
@@ -134,7 +134,7 @@ const useModelCount = ({ totalCount, filteredCount, data, table, loading }) => {
     data,
     state.filters,
     isOfficialProviderActive,
-    officialOnlyCounts.officialProviders,
+    officialOnlyCounts.maintainersHighlight,
   ]);
 };
 

frontend/src/pages/LeaderboardPage/components/Leaderboard/components/Filters/Filters.js

@@ -781,18 +781,18 @@ const LeaderboardFilters = ({
                           <FilterTag
                             label={filter.label}
                             checked={
-                              filter.value === "is_official_provider"
+                              filter.value === "is_highlighted_by_maintainer"
                                 ? isOfficialProviderActive
                                 : selectedBooleanFilters.includes(filter.value)
                             }
                             onChange={
-                              filter.value === "is_official_provider"
+                              filter.value === "is_highlighted_by_maintainer"
                                 ? handleOfficialProviderToggle
                                 : () => handleBooleanFilterToggle(filter.value)
                             }
                             count={
-                              filter.value === "is_official_provider"
-                                ? currentCounts.officialProviders
+                              filter.value === "is_highlighted_by_maintainer"
+                                ? currentCounts.maintainersHighlight
                                 : 0
                             }
                             showCheckbox={true}
@@ -815,7 +815,7 @@ const LeaderboardFilters = ({
                                 borderRadius: "50%",
                                 backgroundColor: (
                                   filter.value ===
-                                  "is_official_provider"
+                                  "is_highlighted_by_maintainer"
                                     ? isOfficialProviderActive
                                     : selectedBooleanFilters.includes(
                                         filter.value
@@ -826,7 +826,7 @@ const LeaderboardFilters = ({
                               }}
                             />
                             {(
-                              filter.value === "is_official_provider"
+                              filter.value === "is_highlighted_by_maintainer"
                                 ? isOfficialProviderActive
                                 : selectedBooleanFilters.includes(filter.value)
                             )

frontend/src/pages/LeaderboardPage/components/Leaderboard/components/Filters/QuickFilters.js

@@ -206,7 +206,7 @@ const QuickFilters = ({ totalCount = 0, loading = false }) => {
               label={officialProvidersPreset.label}
               checked={isOfficialProviderActive}
               onChange={handleOfficialProviderToggle}
-              count={currentCounts.officialProviders}
+              count={currentCounts.maintainersHighlight}
               totalCount={totalCount}
               showCheckbox={true}
               variant="secondary"

frontend/src/pages/LeaderboardPage/components/Leaderboard/components/Filters/hooks/useOfficialProvidersMode.js

@@ -23,7 +23,7 @@ export const useOfficialProvidersMode = () => {
 
     const filters = searchParams.get("filters");
     const isHighlighted =
-      filters?.includes("is_official_provider") || false;
+      filters?.includes("is_highlighted_by_maintainer") || false;
 
     // On initial load
     if (isInitialLoadRef.current) {
@@ -33,7 +33,7 @@ export const useOfficialProvidersMode = () => {
       if (isHighlighted && filters) {
         const initialNormalFilters = filters
           .split(",")
-          .filter((f) => f !== "is_official_provider" && f !== "")
+          .filter((f) => f !== "is_highlighted_by_maintainer" && f !== "")
           .filter(Boolean);
         if (initialNormalFilters.length > 0) {
           normalFiltersRef.current = initialNormalFilters.join(",");
@@ -70,7 +70,7 @@ export const useOfficialProvidersMode = () => {
       const currentFiltersStr = searchParams.get("filters");
       const currentFilters =
         currentFiltersStr?.split(",").filter(Boolean) || [];
-      const highlightFilter = "is_official_provider";
+      const highlightFilter = "is_highlighted_by_maintainer";
       const newSearchParams = new URLSearchParams(searchParams);
 
       if (currentFilters.includes(highlightFilter)) {

frontend/src/pages/LeaderboardPage/components/Leaderboard/constants/defaults.js

@@ -59,14 +59,14 @@ const FILTERS = {
       hide: true,
     },
     {
-      value: "is_official_provider",
+      value: "is_highlighted_by_maintainer",
       label: "Only Official Providers",
       hide: false,
     },
   ],
   HIGHLIGHT_OPTIONS: [
     {
-      value: "is_official_provider",
+      value: "is_highlighted_by_maintainer",
       label: "Only Official Providers",
     },
   ],
@@ -237,7 +237,7 @@ const COLUMNS = {
       defaultVisible: false,
       label: "Hub Availability",
     },
-    "features.is_official_provider": {
+    "features.is_highlighted_by_maintainer": {
       group: "additional_info",
       size: COLUMN_SIZES.OFFICIAL_PROVIDER,
       defaultVisible: false,

frontend/src/pages/LeaderboardPage/components/Leaderboard/constants/quickFilters.js

@@ -45,7 +45,7 @@ export const QUICK_FILTER_PRESETS = [
     shortDescription: 'Officially provided models',
     description: 'Models that are officially provided and maintained by official creators or organizations.',
     filters: {
-      selectedBooleanFilters: ['is_official_provider']
+      selectedBooleanFilters: ['is_highlighted_by_maintainer']
     }
   }
 ]; 

frontend/src/pages/LeaderboardPage/components/Leaderboard/constants/tooltips.js

@@ -258,7 +258,7 @@ export const COLUMN_TOOLTIPS = {
         "For detailed information about our CO₂ calculation methodology, visit:",
       subItems: [
         <a
-          href="https://huggingface.co/docs/leaderboards/open_llm_leaderboard/emissions"
+          href="https://huggingface.co/docs/hub/carbon-emissions"
           target="_blank"
           rel="noopener noreferrer"
           style={{ color: "#90caf9" }}

frontend/src/pages/LeaderboardPage/components/Leaderboard/context/LeaderboardContext.js

@@ -47,7 +47,7 @@ const createInitialCounts = () => {
   return {
     modelTypes,
     precisions,
-    officialProviders: 0,
+    maintainersHighlight: 0,
     mixtureOfExperts: 0,
     flagged: 0,
     merged: 0,
@@ -129,7 +129,7 @@ const modelMatchesFilters = (model, filters) => {
       const filterValue = typeof filter === "object" ? filter.value : filter;
 
       // Maintainer's Highlight keeps positive logic
-      if (filterValue === "is_official_provider") {
+      if (filterValue === "is_highlighted_by_maintainer") {
         return model.features[filterValue];
       }
 
@@ -187,8 +187,8 @@ const calculateModelCounts = (models) => {
 
   models.forEach((model) => {
     const isOfficial =
-      model.features?.is_official_provider ||
-      model.metadata?.is_official_provider;
+      model.features?.is_highlighted_by_maintainer ||
+      model.metadata?.is_highlighted_by_maintainer;
     const countsToUpdate = [normalCounts];
 
     if (isOfficial) {
@@ -214,10 +214,10 @@ const calculateModelCounts = (models) => {
 
       // Boolean filters
       if (
-        model.features?.is_official_provider ||
-        model.metadata?.is_official_provider
+        model.features?.is_highlighted_by_maintainer ||
+        model.metadata?.is_highlighted_by_maintainer
       )
-        counts.officialProviders++;
+        counts.maintainersHighlight++;
       if (model.features?.is_moe || model.metadata?.is_moe)
         counts.mixtureOfExperts++;
       if (model.features?.is_flagged || model.metadata?.is_flagged)

frontend/src/pages/LeaderboardPage/components/Leaderboard/hooks/useDataUtils.js

@@ -58,8 +58,8 @@ export const useProcessedData = (data, averageMode, visibleColumns) => {
         ...item.features,
         is_moe: Boolean(item.features.is_moe),
         is_flagged: Boolean(item.features.is_flagged),
-        is_official_provider: Boolean(
-          item.features.is_official_provider
+        is_highlighted_by_maintainer: Boolean(
+          item.features.is_highlighted_by_maintainer
         ),
         is_merged: Boolean(item.features.is_merged),
         is_not_available_on_hub: Boolean(item.features.is_not_available_on_hub),
@@ -117,8 +117,8 @@ export const useFilteredData = (
     if (isOfficialProviderActive) {
       filteredUnpinned = filteredUnpinned.filter(
         (row) =>
-          row.features?.is_official_provider ||
-          row.metadata?.is_official_provider
+          row.features?.is_highlighted_by_maintainer ||
+          row.metadata?.is_highlighted_by_maintainer
       );
     }
 
@@ -197,7 +197,7 @@ export const useFilteredData = (
             typeof filter === "object" ? filter.value : filter;
 
           // Maintainer's Highlight keeps positive logic
-          if (filterValue === "is_official_provider") {
+          if (filterValue === "is_highlighted_by_maintainer") {
             return row.features[filterValue];
           }
 

frontend/src/pages/LeaderboardPage/components/Leaderboard/utils/columnUtils.js

@@ -1003,18 +1003,18 @@ export const createColumns = (
       ],
     },
     {
-      accessorKey: "features.is_official_provider",
+      accessorKey: "features.is_highlighted_by_maintainer",
       header: createHeaderCell(
         "Official Providers",
         "Models that are officially provided and maintained by their original creators or organizations"
       ),
       cell: ({ row }) => (
         <BooleanValue
-          value={row.original.features.is_official_provider}
+          value={row.original.features.is_highlighted_by_maintainer}
         />
       ),
       size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "features.is_official_provider"
+        "features.is_highlighted_by_maintainer"
       ],
       enableSorting: true,
     },
@@ -1061,7 +1061,7 @@ export const createColumns = (
           "metadata.base_model": 10,
           "model.has_chat_template": 11,
           "features.is_not_available_on_hub": 12,
-          "features.is_official_provider": 13,
+          "features.is_highlighted_by_maintainer": 13,
           "features.is_moe": 14,
           "features.is_flagged": 15,
         };