Instructions to use ydshieh/tiny-random-BertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-BertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="ydshieh/tiny-random-BertForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-BertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("ydshieh/tiny-random-BertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#9
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 sha256:59f5953bd2e114496e200379807dfd4fbb8e13e01e3bd62dd79bed434fecf431
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size 361450
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