switch automodel for automodelforseqclass

README.md

@@ -71,7 +71,7 @@ EmCoder uses the `ModernBERT` tokenizer for correct token-to-embedding mapping.
 Ensure you allow remote code execution since it's a custom architecture.
 ```python
 import torch
-from transformers import AutoModel, AutoTokenizer
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 repo_id = "yezdata/EmCoder"
 
@@ -79,7 +79,7 @@ repo_id = "yezdata/EmCoder"
 tokenizer = AutoTokenizer.from_pretrained("answerdotai/ModernBERT-base")
 
 # Initialize with same config as training
-model = AutoModel.from_pretrained(repo_id, trust_remote_code=True)
+model = AutoModelForSequenceClassification.from_pretrained(repo_id, trust_remote_code=True)
 ```
 ### 2. Bayesian inference
 To obtain probabilistic outputs and uncertainty metrics, use the `mc_forward` method: