Update README.md

README.md

@@ -12,19 +12,24 @@ An [adapter](https://adapterhub.ml) for the `None` model that was trained on the
 
 This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
 
+**Dec 2023 Update:**
+
+Model usage updated to be compatible with latest versions of transformers and adapters (newly released update to adapter-transformers) libraries.
+
+
 ## Usage
 
-First, install `adapter-transformers`:
+First, install `adapters`:
 
 ```
-pip install -U adapter-transformers
+pip install -U adapters
 ```
-_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. [More](https://docs.adapterhub.ml/installation.html)_
+_Note: adapters is built as an add-on to transformers that acts as a drop-in replacement with adapter support. [More](https://docs.adapterhub.ml)_
 
 Now, the adapter can be loaded and activated like this:
 
 ```python
-from transformers import AutoAdapterModel
+from adapters import AutoAdapterModel
 
 model = AutoAdapterModel.from_pretrained("allenai/specter2_aug2023refresh_base")
 adapter_name = model.load_adapter("allenai/specter2_aug2023refresh_classification", source="hf", set_active=True)
@@ -92,13 +97,14 @@ It builds on the work done in [SciRepEval: A Multi-Format Benchmark for Scientif
 *Retrieval model should suffice for downstream task types not mentioned above
 
 ```python
-from transformers import AutoTokenizer, AutoModel
+from transformers import AutoTokenizer
+from adapters import AutoAdapterModel
 
 # load model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained('allenai/specter2_aug2023refresh_base')
 
 #load base model
-model = AutoModel.from_pretrained('allenai/specter2_aug2023refresh_base')
+model = AutoAdapterModel.from_pretrained('allenai/specter2_aug2023refresh_base')
 
 #load the adapter(s) as per the required task, provide an identifier for the adapter in load_as argument and activate it
 model.load_adapter("allenai/specter2_aug2023refresh_classification", source="hf", load_as="specter2_classification", set_active=True)