Instructions to use MSLars/de_longformer_abstr_summ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MSLars/de_longformer_abstr_summ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MSLars/de_longformer_abstr_summ")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MSLars/de_longformer_abstr_summ") model = AutoModelForTokenClassification.from_pretrained("MSLars/de_longformer_abstr_summ", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MSLars/de_longformer_abstr_summ: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/MSLars/de_longformer_abstr_summ/resolve/main/training_args.bin
- Command line
-
hf download hf://MSLars/de_longformer_abstr_summ/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MSLars/de_longformer_abstr_summ/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 4d2e9b68b124bdcb7de7862ff901c7493b5476d846f627a8abe7febf632f1e71
- Size of remote file:
- 4.73 kB
- SHA256:
- 2289b96e177f7c11803fec37254e545bfcca8f6c1535874bfa6bf1d814ea15b4
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