Instructions to use binhquoc/deberta-v1-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binhquoc/deberta-v1-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binhquoc/deberta-v1-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("binhquoc/deberta-v1-base") model = AutoModelForMaskedLM.from_pretrained("binhquoc/deberta-v1-base") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("binhquoc/deberta-v1-base")
model = AutoModelForMaskedLM.from_pretrained("binhquoc/deberta-v1-base")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="binhquoc/deberta-v1-base")