Summarization
Transformers
PyTorch
TensorBoard
Danish
mt5
text2text-generation
Generated from Trainer
Instructions to use RyeAI/DaMedSum-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RyeAI/DaMedSum-large 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="RyeAI/DaMedSum-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RyeAI/DaMedSum-large") model = AutoModelForSeq2SeqLM.from_pretrained("RyeAI/DaMedSum-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RyeAI/DaMedSum-large: direct link, hf CLI and curl.
- Browser
- Download file 4.14 kB
-
https://huggingface.co/RyeAI/DaMedSum-large/resolve/main/training_args.bin
- Command line
-
hf download hf://RyeAI/DaMedSum-large/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RyeAI/DaMedSum-large/resolve/main/training_args.bin
4.14 kB
- Xet hash:
- 05ae0075d5f91c87252617ac2353a6f07262c4cd88a5f1711386403c5b933f54
- Size of remote file:
- 4.14 kB
- SHA256:
- 2b8fac1e7f250cba60a83b34207de2d0322eabfce5182ca094e222834b01fe0a
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