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") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d43d5ec6b52917e73af7a22bfdb205319d00e221afdf4f51fce4e46b3761b151
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size 7819076
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