Update README.md

README.md

@@ -13,7 +13,7 @@ metrics:
 - f1
 - worst_group_accuracy
 model-index:
-- name: davanstrien/modernbert-topics-1m
+- name: davanstrien/ModernBERT-web-topics-1m
   results:
   - task:
       type: text-classification
@@ -157,7 +157,7 @@ Example usage:
 # Use a pipeline as a high-level helper
 from transformers import pipeline
 
-pipe = pipeline("text-classification", model="davanstrien/modernbert-topics-1m")
+pipe = pipeline("text-classification", model="davanstrien/ModernBERT-web-topics-1m")
 
 # direct use
 
@@ -165,7 +165,7 @@ from transformers import AutoModelForSequenceClassification, AutoTokenizer
 import torch
 
 # Load model and tokenizer
-model_name = "davanstrien/modernbert-topics-1m"
+model_name = "davanstrien/ModernBERT-web-topics-1m"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
 
@@ -199,7 +199,7 @@ import torch
 import torch.nn.functional as F
 
 # Load the model with vLLM
-llm = LLM(model="davanstrien/modernbert-topics-1m", task="classify")
+llm = LLM(model="davanstrien/ModernBERT-web-topics-1m", task="classify")
 
 # Single prediction
 text = "This article discusses various approaches to content categorization using machine learning"
@@ -219,7 +219,7 @@ from toolz import keymap
 id2label = (
     httpx.get(
         hf_hub_url(
-            "davanstrien/modernbert-topics-1m", 
+            "davanstrien/ModernBERT-web-topics-1m", 
             filename="config.json"
         )
     )