Instructions to use mohammedbriman/bart-base-finetuned-cnn-dm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammedbriman/bart-base-finetuned-cnn-dm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mohammedbriman/bart-base-finetuned-cnn-dm") model = AutoModelForSeq2SeqLM.from_pretrained("mohammedbriman/bart-base-finetuned-cnn-dm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mohammedbriman/bart-base-finetuned-cnn-dm: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/mohammedbriman/bart-base-finetuned-cnn-dm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mohammedbriman/bart-base-finetuned-cnn-dm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mohammedbriman/bart-base-finetuned-cnn-dm/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- cd028688cb7d9df1a28daa30317ec42acfe05d2640100c7442fb89278fe1525d
- Size of remote file:
- 558 MB
- SHA256:
- 21515425af34fe9dba773439aed6e7adb6d49ca3cd572564142f980f14a747f6
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