Instructions to use tomato/electra-Question-answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomato/electra-Question-answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tomato/electra-Question-answer")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("tomato/electra-Question-answer") model = AutoModelForQuestionAnswering.from_pretrained("tomato/electra-Question-answer") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("tomato/electra-Question-answer")
model = AutoModelForQuestionAnswering.from_pretrained("tomato/electra-Question-answer")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="tomato/electra-Question-answer")