Instructions to use whu9/multi_doc_sum_slide_token with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whu9/multi_doc_sum_slide_token with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, NetSum tokenizer = AutoTokenizer.from_pretrained("whu9/multi_doc_sum_slide_token") model = NetSum.from_pretrained("whu9/multi_doc_sum_slide_token", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from whu9/multi_doc_sum_slide_token: direct link, hf CLI and curl.
- Browser
- Download file 2.1 GB
-
https://huggingface.co/whu9/multi_doc_sum_slide_token/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://whu9/multi_doc_sum_slide_token/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/whu9/multi_doc_sum_slide_token/resolve/main/pytorch_model.bin
2.1 GB
- Xet hash:
- 941f68276d2dcc9fb76af0f243505ab8d18390265928cae34a52ce71c1b43e57
- Size of remote file:
- 2.1 GB
- SHA256:
- be72f0739bc84beecc07c825bc42c4850bff9e780b4eedccf5b4c11ce594b3d4
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