Instructions to use Sayan01/tiny-bert-mrpc-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sayan01/tiny-bert-mrpc-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sayan01/tiny-bert-mrpc-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sayan01/tiny-bert-mrpc-distilled") model = AutoModelForSequenceClassification.from_pretrained("Sayan01/tiny-bert-mrpc-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9edeb1d983e2b5cae243365b47004a5cacfa74e184e3be4b0adbca08e1cb34e1
- Size of remote file:
- 57.4 MB
- SHA256:
- c44d20bda9111e7b1c03ff5dba002d16a15fe7b516bbb9a7df42ee5b139c1539
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