Instructions to use routellm/bert_mmlu_augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use routellm/bert_mmlu_augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="routellm/bert_mmlu_augmented")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("routellm/bert_mmlu_augmented") model = AutoModelForSequenceClassification.from_pretrained("routellm/bert_mmlu_augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eadad2301bc861b857f55acaf20bdf1f1e976af5617c5ac6450c6f4b30aabc2c
- Size of remote file:
- 2.22 GB
- SHA256:
- 292ab62ae708a601fc25279d6d873bf5d117448605f17f9f16d28646e8803292
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