Instructions to use Data255FinalProj/deberta-saumya-tune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Data255FinalProj/deberta-saumya-tune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Data255FinalProj/deberta-saumya-tune")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Data255FinalProj/deberta-saumya-tune") model = AutoModelForQuestionAnswering.from_pretrained("Data255FinalProj/deberta-saumya-tune") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("Data255FinalProj/deberta-saumya-tune")
model = AutoModelForQuestionAnswering.from_pretrained("Data255FinalProj/deberta-saumya-tune")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Data255FinalProj/deberta-saumya-tune")