Instructions to use zedalef/bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zedalef/bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zedalef/bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zedalef/bert") model = AutoModelForSequenceClassification.from_pretrained("zedalef/bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63c2ec778bbecb6c38bbcbeb5cd930aabb9017458c33d69e39e5882933fbb64d
- Size of remote file:
- 433 MB
- SHA256:
- f1db85ba6fa9dab82b64d6158ecfa3864571747aa87f898726d7f34f3ecc345e
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