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")# pip install -U transformers accelerate # 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
# pip install -U transformers accelerate
# 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")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-adapters")