Instructions to use Reza-Madani/mini-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Reza-Madani/mini-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Reza-Madani/mini-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Reza-Madani/mini-bert") model = AutoModelForSequenceClassification.from_pretrained("Reza-Madani/mini-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20abe0ac1979111f01a7d80fa2c78771b29530e2c1a948954f22bfbb1008199b
- Size of remote file:
- 44.7 MB
- SHA256:
- b70f5abfe5ba3a135e2ad8b3d50e05c03e0697d9aeaa5d7cc2ab8fc52b0f058b
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