Instructions to use stevemobs/deberta-base-finetuned-aqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevemobs/deberta-base-finetuned-aqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="stevemobs/deberta-base-finetuned-aqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("stevemobs/deberta-base-finetuned-aqa") model = AutoModelForQuestionAnswering.from_pretrained("stevemobs/deberta-base-finetuned-aqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb271ca104b2a953aa3e963bf5c847f5988d5bf21deea472292d7dec3933737c
- Size of remote file:
- 3.25 kB
- SHA256:
- ba6b3269fa2219912f71ab72a5bfa79f98e894e70853f190aab800c84073b883
路
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