Instructions to use abragin/bert_book_zipper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abragin/bert_book_zipper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abragin/bert_book_zipper")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abragin/bert_book_zipper") model = AutoModelForSequenceClassification.from_pretrained("abragin/bert_book_zipper") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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:f99c72ebbfbf803f387264e945bbf91f874297f9709d28aac703d2acd20b7c68
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size 669465704
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