Instructions to use shahidul034/sentence_equivalent_check with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahidul034/sentence_equivalent_check with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shahidul034/sentence_equivalent_check")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shahidul034/sentence_equivalent_check") model = AutoModelForSequenceClassification.from_pretrained("shahidul034/sentence_equivalent_check") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba7500cb8bb49b75567f926f8a40c0b985e02a0a189e0d5bb56c4b67c9eb9839
- Size of remote file:
- 5.12 kB
- SHA256:
- 93f51ffbcca2e5b140e519081fc128e388425735ef76807928aa6fb892b2142c
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