Adapt for layerd: Change hardcoded size from 1024 to 512 (line 56) and add trained weights

birefnet.py

@@ -53,7 +53,7 @@ class Config(PretrainedConfig):
             }[self.task]
         ][1]    # choose 0 to skip
         self.lr = (1e-4 if 'DIS5K' in self.task else 1e-5) * math.sqrt(self.batch_size / 4)     # DIS needs high lr to converge faster. Adapt the lr linearly
-        self.size = 1024
+        self.size = 512
         self.num_workers = max(4, self.batch_size)          # will be decrease to min(it, batch_size) at the initialization of the data_loader
 
         # Backbone settings

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:28416acdaedc3fbee0f80f888893a2fdca60ae81b1b27a41433a4e791598e330
+size 884878824