Instructions to use Nandhakumar370/bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nandhakumar370/bert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Nandhakumar370/bert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Nandhakumar370/bert-tiny") model = AutoModelForSequenceClassification.from_pretrained("Nandhakumar370/bert-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 618a6be88555a0bbd57b5d08f2c1da3662c5ec1a17936da36d7cccca60d21908
- Size of remote file:
- 17.7 MB
- SHA256:
- c032c4fffee1a85a017d5b5ba4d9cf9b6cd1e2deb73e78d50f8ea55e5ac7e0fc
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