Instructions to use cuongtran/BARTTextSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cuongtran/BARTTextSummarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cuongtran/BARTTextSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("cuongtran/BARTTextSummarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from cuongtran/BARTTextSummarization: direct link, hf CLI and curl.
- Browser
- Download file 1.68 GB
-
https://huggingface.co/cuongtran/BARTTextSummarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://cuongtran/BARTTextSummarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cuongtran/BARTTextSummarization/resolve/main/pytorch_model.bin
1.68 GB
- Xet hash:
- 709898a98b07585ee2aa1f48a1ad47c3ce46a493ba949151af613017b4d0eff5
- Size of remote file:
- 1.68 GB
- SHA256:
- d3166bbe19d118f84de499c45f73cba1c7e1e9ef616f85096e84e4b8a75e0994
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