Instructions to use routellm/bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use routellm/bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="routellm/bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("routellm/bert") model = AutoModelForSequenceClassification.from_pretrained("routellm/bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c65323a7f6b22909b9cb73a63b6a6f6f4b9b67ef29e6cea0963cacd83f6c8e6
- Size of remote file:
- 5.05 kB
- SHA256:
- 95e920ae5dfe8aafcffdadba372ebdebe96c9ae3dd7d6c5a09767311863b84f6
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