Instructions to use sileod/deberta-v3-base-tasksource-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-base-tasksource-adapters with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-adapters")# Load model directly from transformers import AutoTokenizer, Adapter tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-base-tasksource-adapters") model = Adapter.from_pretrained("sileod/deberta-v3-base-tasksource-adapters", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
language:
- en
pipeline_tag: text-classification
!pip install tasknet tasksource
import tasknet as tn
pipe = tn.load_pipeline('sileod/deberta-v3-base-tasksource-nli','glue/sst2') # works for 500+ tasksource tasks
pipe(['That movie was great !', 'Awful movie.'])