Instructions to use AmirMohseni/BERT-Router-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmirMohseni/BERT-Router-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AmirMohseni/BERT-Router-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AmirMohseni/BERT-Router-base") model = AutoModelForSequenceClassification.from_pretrained("AmirMohseni/BERT-Router-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bf94ba57f2feb0a1467e66cd8947d4d8e681625d2e0d0f55d95a8052653ac7c
- Size of remote file:
- 5.24 kB
- SHA256:
- 1f157d7f009b48ffb48b3cd65ad0ad39d5af68ec03a84063cb436ed965dd153f
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