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:
- 721f4e3909bf116a65707c8cba52e2fb9fc18ad3ee244d0d923285ba8a3e38a3
- Size of remote file:
- 3.52 kB
- SHA256:
- 18440b93c58301c2597f9a4b14aced7a37a0122482e207080dc6b74ecc1f5dd2
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