Instructions to use hz53/bert-base-uncased-cb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hz53/bert-base-uncased-cb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hz53/bert-base-uncased-cb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hz53/bert-base-uncased-cb") model = AutoModelForSequenceClassification.from_pretrained("hz53/bert-base-uncased-cb") - 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 sha256:1b8ebf08d59ad7df8a1ff4de1a832be08d0e985465c313e951c68dc0cf9670d5
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size 437965908
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