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config.json

@@ -1,30 +1,20 @@
-from modeling import KinaseSubstrateConfig, KinaseSubstrateModel
-import torch
-
-# Build config
-config = KinaseSubstrateConfig(
-    tape_model_name="bert-base",
-    num_labels=2,
-    threshold=ckpt["threshold"],   # from your checkpoint
-    with_sep=True,
-    max_len=1024,
-    # Tell HF where to find the custom classes:
-    auto_map={
-        "AutoConfig": "modeling.KinaseSubstrateConfig",
-        "AutoModel": "modeling.KinaseSubstrateModel",
-    },
-    custom_pipelines={
-        "kinase-substrate": {
-            "impl": "pipeline.KinaseSubstratePipeline",
-            "pt": ["AutoModel"],
-        }
-    },
-)
-
-# Build and load model
-model = KinaseSubstrateModel(config)
-model.backbone.load_state_dict(ckpt["state_dict"])  # load your trained weights
-
-# Save
-model.save_pretrained("./my_kinase_model")
-config.save_pretrained("./my_kinase_model")
+{
+  "model_type": "kinase_substrate_bert",
+  "tape_model_name": "bert-base",
+  "num_labels": 2,
+  "threshold": 0.7734375,
+  "with_sep": true,
+  "max_len": 1024,
+  "auto_map": {
+    "AutoConfig": "modeling.KinaseSubstrateConfig",
+    "AutoModel": "modeling.KinaseSubstrateModel"
+  },
+  "custom_pipelines": {
+    "kinase-substrate": {
+      "impl": "pipeline.KinaseSubstratePipeline",
+      "pt": [
+        "AutoModel"
+      ]
+    }
+  }
+}