Instructions to use michaelrglass/bert-base-uncased-sspt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelrglass/bert-base-uncased-sspt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="michaelrglass/bert-base-uncased-sspt")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("michaelrglass/bert-base-uncased-sspt") model = AutoModelForQuestionAnswering.from_pretrained("michaelrglass/bert-base-uncased-sspt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit 路
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Parent(s): 611f8ad
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d8a73a45d8ed9aa4082572cb1f6a8fbb32f05845ebed6dfcaa121f0487d3db4
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size 435579886
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