Instructions to use xihajun/20_bert_base_pruned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xihajun/20_bert_base_pruned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="xihajun/20_bert_base_pruned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("xihajun/20_bert_base_pruned") model = AutoModelForQuestionAnswering.from_pretrained("xihajun/20_bert_base_pruned") - 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 sha256:644fd21c338cc0039de21e63c66741d3205b9e80bc85e417472a1dea33f506e4
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size 363960880
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