Instructions to use NightMachinery/task_adapter_amazon_xlm_roberta_base_en_wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use NightMachinery/task_adapter_amazon_xlm_roberta_base_en_wiki with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("xlm-roberta-base") model.load_adapter("NightMachinery/task_adapter_amazon_xlm_roberta_base_en_wiki", set_active=True) - Notebooks
- Google Colab
- Kaggle
Adapter NightMachinery/task_adapter_amazon_xlm_roberta_base_en_wiki for xlm-roberta-base
An adapter for the xlm-roberta-base 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:
pip install -U 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:
from transformers import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("xlm-roberta-base")
adapter_name = model.load_adapter("NightMachinery/task_adapter_amazon_xlm_roberta_base_en_wiki", source="hf", set_active=True)
Architecture & Training
Evaluation results
Citation
- Downloads last month
- 5
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support