Instructions to use Danish-summarisation/DanSumT5-pilot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Danish-summarisation/DanSumT5-pilot with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="Danish-summarisation/DanSumT5-pilot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Danish-summarisation/DanSumT5-pilot") model = AutoModelForSeq2SeqLM.from_pretrained("Danish-summarisation/DanSumT5-pilot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Danish-summarisation/DanSumT5-pilot: direct link, hf CLI and curl.
- Browser
- Download file 1.95 GB
-
https://huggingface.co/Danish-summarisation/DanSumT5-pilot/resolve/main/optimizer.pt
- Command line
-
hf download hf://Danish-summarisation/DanSumT5-pilot/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Danish-summarisation/DanSumT5-pilot/resolve/main/optimizer.pt
1.95 GB
- Xet hash:
- fbfa1277167d00d4701be5527c0e9f9164477c7176f04a41ae2ad5ed0462590e
- Size of remote file:
- 1.95 GB
- SHA256:
- fc91e2fa415ded95ce0b768fcf744fde086c771a2610643122ac4a93e015b460
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