Update model - Task: default

AttrMaskMolecularEncoder.pt

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+oid sha256:faf06cb24eb95d1ba0bc360e5af360ecc0f88c193f9129615f721ef88522121b
+size 14545405

README.md

@@ -1,75 +1,74 @@
----
-tags:
-- torch_molecule
-- molecular-property-prediction
-library_name: torch_molecule
----
-
-# MoamaMolecularEncoder Model
-
-## Model Description
-- **Model Type**: MoamaMolecularEncoder
-- **Framework**: torch_molecule
-- **Last Updated**: 2025-07-28
-
-## Task Summary
-| Task | Version | Last Updated | Parameters | Metrics |
-|------|---------|--------------|------------|----------|
-| default | 0.0.5 | 2025-07-28 | 3,832,927 |  |
-
-
-## Usage
-
-```python
-from torch_molecule import MoamaMolecularEncoder
-
-# Load model for specific task
-model = MoamaMolecularEncoder()
-model.load(
-    "local_model_dir/MoamaMolecularEncoder.pt",
-    repo="Do1Yun/TorchMoleculeEncoderRepo"
-)
-
-# For predictor: Make predictions
-# predictions = model.predict(smiles_list)
-# For generator: Make generations
-# generations = model.generate(n_samples)
-# For encoder: Make encodings
-# encodings = model.encode(smiles_list)
-```
-
-## Tasks Details
-
-
-### default Task
-- **Current Version**: 0.0.5
-- **Last Updated**: 2025-07-28
-- **Parameters**: 3,832,927
-- **Configuration**:
-```python
-{
-  "mask_rate": 0.15,
-  "lw_rec": 0.5,
-  "encoder_type": "gin-virtual",
-  "readout": "sum",
-  "num_layer": 5,
-  "hidden_size": 300,
-  "drop_ratio": 0.5,
-  "norm_layer": "batch_norm",
-  "batch_size": 128,
-  "epochs": 500,
-  "learning_rate": 0.001,
-  "weight_decay": 0.0,
-  "grad_clip_value": null,
-  "use_lr_scheduler": false,
-  "scheduler_factor": 0.5,
-  "scheduler_patience": 5,
-  "fitting_epoch": 499,
-  "device": {
-    "_type": "unknown",
-    "repr": "cuda:0"
-  },
-  "verbose": false,
-  "model_name": "MoamaMolecularEncoder"
-}
-```
+---
+tags:
+- torch_molecule
+library_name: torch_molecule
+---
+
+# AttrMaskMolecularEncoder Model
+
+## Model Description
+- **Model Type**: AttrMaskMolecularEncoder
+- **Framework**: torch_molecule
+- **Last Updated**: 2025-07-28
+
+## Task Summary
+| Task | Version | Last Updated | Parameters | Metrics |
+|------|---------|--------------|------------|----------|
+| default | 0.0.6 | 2025-07-28 | 3,594,425 |  |
+
+
+## Usage
+
+```python
+from torch_molecule import AttrMaskMolecularEncoder
+
+# Load model for specific task
+model = AttrMaskMolecularEncoder()
+model.load(
+    "local_model_dir/AttrMaskMolecularEncoder.pt",
+    repo="Do1Yun/TorchMoleculeEncoderRepo"
+)
+
+# For predictor: Make predictions
+# predictions = model.predict(smiles_list)
+# For generator: Make generations
+# generations = model.generate(n_samples)
+# For encoder: Make encodings
+# encodings = model.encode(smiles_list)
+```
+
+## Tasks Details
+
+
+### default Task
+- **Current Version**: 0.0.6
+- **Last Updated**: 2025-07-28
+- **Parameters**: 3,594,425
+- **Configuration**:
+```python
+{
+  "mask_num": 0,
+  "mask_rate": 0.15,
+  "encoder_type": "gin-virtual",
+  "readout": "sum",
+  "num_layer": 5,
+  "hidden_size": 300,
+  "drop_ratio": 0.5,
+  "norm_layer": "batch_norm",
+  "batch_size": 128,
+  "epochs": 500,
+  "learning_rate": 0.001,
+  "weight_decay": 0.0,
+  "grad_clip_value": null,
+  "use_lr_scheduler": false,
+  "scheduler_factor": 0.5,
+  "scheduler_patience": 5,
+  "fitting_epoch": 499,
+  "device": {
+    "_type": "unknown",
+    "repr": "cuda:0"
+  },
+  "verbose": false,
+  "model_name": "AttrMaskMolecularEncoder"
+}
+```

config.json

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-{
-  "model_name": "AttrMaskMolecularEncoder",
-  "framework": "torch_molecule",
-  "date_created": "2025-07-28T00:54:19.004999",
-  "tasks": {
-    "default": {
-      "versions": [],
-      "current_version": "0.0.5",
-      "date_added": "2025-07-28T00:54:19.007002",
-      "last_updated": "2025-07-28T01:05:14.392742",
-      "num_parameters": 3832927,
-      "config": {
-        "mask_rate": 0.15,
-        "lw_rec": 0.5,
-        "encoder_type": "gin-virtual",
-        "readout": "sum",
-        "num_layer": 5,
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-        "norm_layer": "batch_norm",
-        "batch_size": 128,
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-        "learning_rate": 0.001,
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 }