Upload modeling_fast_esmfold.py with huggingface_hub

modeling_fast_esmfold.py

@@ -1089,7 +1089,6 @@ class FastEsmForProteinFolding(EsmForProteinFolding):
         self,
         sequence: str,
         ttt: bool = False,
-        num_recycles: Optional[int] = None,
         return_pdb_string: bool = True,
     ) -> Dict[str, Any]:
         """Fold a protein sequence, optionally with test-time training.
@@ -1097,7 +1096,6 @@ class FastEsmForProteinFolding(EsmForProteinFolding):
         Args:
             sequence: Protein sequence (single-letter amino acid codes)
             ttt: If True, run test-time training before folding (improves accuracy)
-            num_recycles: Override default number of recycling iterations (None = use config default)
             return_pdb_string: If True, include PDB string in output
 
         Returns:
@@ -1114,7 +1112,7 @@ class FastEsmForProteinFolding(EsmForProteinFolding):
             result["ttt_losses"] = ttt_result["losses"]
 
         with torch.no_grad():
-            output = self.infer(sequence, num_recycles=num_recycles)
+            output = self.infer(sequence)
 
         plddt = output["plddt"]
         if plddt.dim() >= 2: