Instructions to use wesleymorris/summary-longformer-content-da with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesleymorris/summary-longformer-content-da with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wesleymorris/summary-longformer-content-da")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wesleymorris/summary-longformer-content-da") model = AutoModelForSequenceClassification.from_pretrained("wesleymorris/summary-longformer-content-da", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wesleymorris/summary-longformer-content-da: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/wesleymorris/summary-longformer-content-da/resolve/main/training_args.bin
- Command line
-
hf download hf://wesleymorris/summary-longformer-content-da/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wesleymorris/summary-longformer-content-da/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 6252c6ce60602ee8b5bcde56bc7d793ec0eae668a05197bfdcd1efabba3b0a6f
- Size of remote file:
- 3.39 kB
- SHA256:
- fdd5b1eedf0705e6598140d74c020ae31ba6f27e70b073d36e9b9606a14c85d7
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