Instructions to use traberph/RedBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use traberph/RedBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="traberph/RedBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("traberph/RedBERT") model = AutoModelForSequenceClassification.from_pretrained("traberph/RedBERT") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:904ff7c5f7c1b19af037423bba3c79cb8123100bd1df749b38df84ee67c6bba3
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size 359032932
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