Instructions to use Prompsit/paraphrase-bert-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prompsit/paraphrase-bert-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Prompsit/paraphrase-bert-pt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Prompsit/paraphrase-bert-pt") model = AutoModelForSequenceClassification.from_pretrained("Prompsit/paraphrase-bert-pt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Prompsit/paraphrase-bert-pt: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/Prompsit/paraphrase-bert-pt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Prompsit/paraphrase-bert-pt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Prompsit/paraphrase-bert-pt/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- fc8f2754866fa4b8c8163cf6b60c1ef383fc02a3dac4b4013e19b95d7f4f0af0
- Size of remote file:
- 436 MB
- SHA256:
- bff4e0b43c243a7e7668cee0be15c0e062f237164ed8393bfac8d5ad73397f15
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