
# Adapter `domadapter/joint_dt_camera_photo_apparel` for bert-base-uncased

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

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

## Usage

First, install `adapter-transformers`:

```
pip install -U adapter-transformers
```
_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)_

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

```python
from transformers import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("bert-base-uncased")
adapter_name = model.load_adapter("domadapter/joint_dt_camera_photo_apparel", source="hf", set_active=True)
```

## Architecture & Training

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## Evaluation results

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## Citation

<!-- Add some description here -->
{"tags": ["bert", "adapter-transformers", "adapterhub:sentiment/amazon"], "datasets": ["amazon"]}
adapter-transformers bert adapterhub:sentiment/amazon dataset:amazon region:us
TAGS
#adapter-transformers #bert #adapterhub-sentiment/amazon #dataset-amazon #region-us 


# Adapter 'domadapter/joint_dt_camera_photo_apparel' for bert-base-uncased

An adapter for the 'bert-base-uncased' model that was trained on the sentiment/amazon dataset and includes a prediction head for classification.

This adapter was created for usage with the adapter-transformers library.

## Usage

First, install 'adapter-transformers':


_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More_

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



## Architecture & Training



## Evaluation results




# Adapter 'domadapter/joint_dt_camera_photo_apparel' for bert-base-uncased

An adapter for the 'bert-base-uncased' model that was trained on the sentiment/amazon dataset and includes a prediction head for classification.

This adapter was created for usage with the adapter-transformers library. ## Usage

First, install 'adapter-transformers':


_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More_

Now, the adapter can be loaded and activated like this: ## Architecture & Training ## Evaluation results
TAGS
#adapter-transformers #bert #adapterhub-sentiment/amazon #dataset-amazon #region-us 
 # Adapter 'domadapter/joint_dt_camera_photo_apparel' for bert-base-uncased

An adapter for the 'bert-base-uncased' model that was trained on the sentiment/amazon dataset and includes a prediction head for classification.

This adapter was created for usage with the adapter-transformers library. ## Usage

First, install 'adapter-transformers':


_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More_

Now, the adapter can be loaded and activated like this: ## Architecture & Training ## Evaluation results
TAGS
#adapter-transformers #bert #adapterhub-sentiment/amazon #dataset-amazon #region-us 
# Adapter 'domadapter/joint_dt_camera_photo_apparel' for bert-base-uncased

An adapter for the 'bert-base-uncased' model that was trained on the sentiment/amazon dataset and includes a prediction head for classification.

This adapter was created for usage with the adapter-transformers library.## Usage

First, install 'adapter-transformers':


_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More_

Now, the adapter can be loaded and activated like this:## Architecture & Training## Evaluation results