Instructions to use aseifert/distilbert-casing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aseifert/distilbert-casing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aseifert/distilbert-casing")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aseifert/distilbert-casing") model = AutoModelForTokenClassification.from_pretrained("aseifert/distilbert-casing") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:2a2015244ec3c31e7839c9f86399ed411ed5be838b0e891855931819927ac86a
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size 267263100
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