---
tags:
- adapter-transformers
- roberta
- adapterhub:sentiment/rotten_tomatoes
datasets:
- rotten_tomatoes
pipeline_tag: text-classification
widget:
- text: "Adapters are awesome" 
---

# Adapter `solwol/my-awesome-adapter` for roberta-base

An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [sentiment/rotten_tomatoes](https://adapterhub.ml/explore/sentiment/rotten_tomatoes/) dataset and includes a prediction head for classification.

This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library.

## Usage

First, install `transformers` and `adapters`:

```
pip install -U transformers adapters
```

Now, the adapter can be loaded and activated like this:

```python
from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("roberta-base")
adapter_name = model.load_adapter("solwol/my-awesome-adapter", source="hf", set_active=True)
adapter_name 
```
Next, to perform sentiment classification:

```python
from transformers import AutoTokenizer, TextClassificationPipeline

tokenizer = AutoTokenizer.from_pretrained("roberta-base")
classifier = TextClassificationPipeline(model=model, tokenizer=tokenizer)
classfifier("Adapters are awesome!")
```