Instructions to use NouraTawil/summodel-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NouraTawil/summodel-bert with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NouraTawil/summodel-bert") model = AutoModelForSeq2SeqLM.from_pretrained("NouraTawil/summodel-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NouraTawil/summodel-bert: direct link, hf CLI and curl.
- Browser
- Download file 1.02 GB
-
https://huggingface.co/NouraTawil/summodel-bert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NouraTawil/summodel-bert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NouraTawil/summodel-bert/resolve/main/pytorch_model.bin
1.02 GB
- Xet hash:
- 51c0649af85d61a82994b11019a29426b89ffc42c624b151e323be2527ca5f38
- Size of remote file:
- 1.02 GB
- SHA256:
- ab299e9ac34ccf2e3f6180e6928853d13aac690cb147871c3075b4d1430edadb
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