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README.md

@@ -1,14 +1,14 @@
 ---
 tags:
 - adapter-transformers
-- bert
+- roberta
 datasets:
 - glue
 ---
 
-# Adapter `WillHeld/pfadapter-bert-base-uncased-tada-values` for bert-base-uncased
+# Adapter `WillHeld/pfadapter-bert-base-uncased-tada-values` for None
 
-An [adapter](https://adapterhub.ml) for the `bert-base-uncased` model that was trained on the [glue](https://huggingface.co/datasets/glue/) dataset.
+An [adapter](https://adapterhub.ml) for the `None` model that was trained on the [glue](https://huggingface.co/datasets/glue/) dataset.
 
 This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
 
@@ -26,7 +26,7 @@ Now, the adapter can be loaded and activated like this:
 ```python
 from transformers import AutoAdapterModel
 
-model = AutoAdapterModel.from_pretrained("bert-base-uncased")
+model = AutoAdapterModel.from_pretrained("None")
 adapter_name = model.load_adapter("WillHeld/pfadapter-bert-base-uncased-tada-values", source="hf", set_active=True)
 ```
 

adapter_config.json

@@ -32,9 +32,9 @@
     "use_gating": false
   },
   "hidden_size": 768,
-  "model_class": "BertAdapterModelForAlignment",
-  "model_name": "bert-base-uncased",
-  "model_type": "bert",
+  "model_class": "RobertaAdapterModel",
+  "model_name": null,
+  "model_type": "roberta",
   "name": "tada_aave",
   "version": "3.2.0a0"
 }

pytorch_adapter.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7ba65619d43c219baa29a89f2d8fd9e88c915e900e86c6c2804b05bf27bf1331
-size 4782429
+oid sha256:8adebf9662dca6cf09b8e47268ae54fc8add05f2b68a7c86e71c2328eaf46acb
+size 4780541