Instructions to use Marco127/BERTCased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marco127/BERTCased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Marco127/BERTCased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Marco127/BERTCased") model = AutoModelForSequenceClassification.from_pretrained("Marco127/BERTCased") - 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 sha256:5b3e3f22cdc5d30e5bc6cf9efab612242ae48e8e42951613558d5a6bcd2dbb2c
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size 442881204
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