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")# pip install -U transformers accelerate # 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
Download scheduler.pt from routellm/bert_mmlu_augmented: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/routellm/bert_mmlu_augmented/resolve/main/scheduler.pt
- Command line
-
hf download hf://routellm/bert_mmlu_augmented/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/routellm/bert_mmlu_augmented/resolve/main/scheduler.pt
1.06 kB
- Xet hash:
- be8b1eeb6ae8ecb0c1299ca11a03c8651f93c92a21166db07dbd81fa4f3f79f4
- Size of remote file:
- 1.06 kB
- SHA256:
- 7500d0256ae6bc9973450089428735ca495c91347af647fa1b59cefa259d5552
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