Instructions to use whu9/multi_doc_sum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whu9/multi_doc_sum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, NetSum tokenizer = AutoTokenizer.from_pretrained("whu9/multi_doc_sum") model = NetSum.from_pretrained("whu9/multi_doc_sum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from whu9/multi_doc_sum: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/whu9/multi_doc_sum/resolve/main/training_args.bin
- Command line
-
hf download hf://whu9/multi_doc_sum/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/whu9/multi_doc_sum/resolve/main/training_args.bin
3.18 kB
- Xet hash:
- 74000874306517646543d9258f408c987888d789005b7908b8c57ad798f9f77d
- Size of remote file:
- 3.18 kB
- SHA256:
- e0fd59d4b8042176f6fab6c163595f7944413fbed5d2378adc5cf25250a910d1
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