Upload adapter model

Model-demo-35M.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:51b87f7a4795357e35d14773de5a42741fe31528af5b006a937dddbb763ad73b
+size 3578581

README.md

@@ -1,11 +1,11 @@
 ---
-library_name: peft
 base_model: westlake-repl/SaProt_35M_AF2
+library_name: peft
 ---
 
 # Model Card for Model ID
 
-This model is used for a demo task<br> The digital label means: <br>0: Nucleus <br>1: Cytoplasm <br>2: Extracellular <br>3: Mitochondrion <br>4: Cell.membrane <br>5: Endoplasmic.reticulum <br>6: Plastid <br>7: Golgi.apparatus <br>8: Lysosome/Vacuole <br>9: Peroxisome <br>
+This model is used for a demo classification task<br><br> The digital label means: <br>0: A <br> 1: B <br> 
 
 
 
@@ -81,7 +81,7 @@ Use the code below to get started with the model.
 
 [More Information Needed]
 
-### Training Procedure 
+### Training Procedure
 
 <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
@@ -197,8 +197,6 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 ## Model Card Contact
 
 [More Information Needed]
-
-
 ### Framework versions
 
 - PEFT 0.10.0

adapter_config.json

@@ -10,8 +10,8 @@
   "layers_pattern": null,
   "layers_to_transform": null,
   "loftq_config": {},
-  "lora_alpha": 8,
-  "lora_dropout": 0.1,
+  "lora_alpha": 16,
+  "lora_dropout": 0.0,
   "megatron_config": null,
   "megatron_core": "megatron.core",
   "modules_to_save": [
@@ -22,11 +22,11 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "key",
+    "intermediate.dense",
     "output.dense",
-    "query",
+    "key",
     "value",
-    "intermediate.dense"
+    "query"
   ],
   "task_type": "SEQ_CLS",
   "use_dora": false,

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:7926a2e85a540575fd2c2e5ad2d20e4ca9b44aaf7a5590a686f9037a4ef2f150
 size 4265400

metadata.json

@@ -0,0 +1,3 @@
+{
+    "training_data_type": "AA"
+}