Text Classification
Transformers
PyTorch
Safetensors
Persian
bert
Persian
paraphrase
paraphrase-identification
ParsBERT
NLP
sequence-classification
text-embeddings-inference
Instructions to use amir1381sa/persian-paraphrase-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amir1381sa/persian-paraphrase-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amir1381sa/persian-paraphrase-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amir1381sa/persian-paraphrase-bert") model = AutoModelForSequenceClassification.from_pretrained("amir1381sa/persian-paraphrase-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from amir1381sa/persian-paraphrase-bert: direct link, hf CLI and curl.
- Browser
- Download file 651 MB
-
https://huggingface.co/amir1381sa/persian-paraphrase-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://amir1381sa/persian-paraphrase-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/amir1381sa/persian-paraphrase-bert/resolve/main/pytorch_model.bin
651 MB
- Xet hash:
- 5aca5c19d1c4ac3f5b21767f7f3057e21ca28148ae5045a1e6d521507c77d80a
- Size of remote file:
- 651 MB
- SHA256:
- f67ad1e6d1b846c547e89080f7f817e20416b4dee6cce52a8588d70eb9bbbf79
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