Instructions to use MiBo/SABERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MiBo/SABERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MiBo/SABERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MiBo/SABERT") model = AutoModelForSequenceClassification.from_pretrained("MiBo/SABERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5c462be4dd682546fcfd65d76da2bb02517c1c61993e4eb882cdb8fb4289389
- Size of remote file:
- 438 MB
- SHA256:
- ac65db8f0d19d111d2768064903ae3ab6b29f51c1d89785953545364efc6a833
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