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
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 sha256:73a50cb0e3ef5cca0970fc6c3d204b08f0840eb33357451c68fc034f74aa5ed8
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size 554441224
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