Instructions to use avkumararun/bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avkumararun/bert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avkumararun/bert-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avkumararun/bert-tiny") model = AutoModelForSequenceClassification.from_pretrained("avkumararun/bert-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9ee10d4ce81d1bbbe4bd85ce2ae0629432b83a18fbd874ac6a236237def4264
- Size of remote file:
- 17.7 MB
- SHA256:
- 146c98a772e96d26aa81ed6dc0c751d958fb5e613c643f0aef93e16cae3bf72f
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