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:
- 0b6964205139da949e7b92bc54eaecd7d42cab42f34b0734d5a10f6a09b0fb41
- Size of remote file:
- 5.05 kB
- SHA256:
- 3e803644b854db4a03dc63967c26b4ceb10d54a86829b2abc030b4adda38cf3c
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