Transformers
PyTorch
Arabic
encoder-decoder
text2text-generation
AraBERT
BERT
BERT2BERT
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
Instructions to use malmarjeh/bert2bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malmarjeh/bert2bert with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("malmarjeh/bert2bert") model = AutoModelForSeq2SeqLM.from_pretrained("malmarjeh/bert2bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from malmarjeh/bert2bert: direct link, hf CLI and curl.
- Browser
- Download file 657 MB
-
https://huggingface.co/malmarjeh/bert2bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://malmarjeh/bert2bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/malmarjeh/bert2bert/resolve/main/pytorch_model.bin
657 MB
- Xet hash:
- 0c7d52e687b7c8e517357321ea96b7e08e0c5144bb92192395301447a9fd25d7
- Size of remote file:
- 657 MB
- SHA256:
- dceeb5a8a01c897a7d7c06777b8b2fce0d66b7066b09415ba69ab46d506bc7f1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.