Summarization
Transformers
PyTorch
TensorBoard
Danish
mt5
text2text-generation
Generated from Trainer
Instructions to use RyeAI/DaMedSumT5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RyeAI/DaMedSumT5-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/DaMedSumT5-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("RyeAI/DaMedSumT5-large") model = AutoModelForSeq2SeqLM.from_pretrained("RyeAI/DaMedSumT5-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fb08a4f81b84b92aca7773a36757f4313dccd510bf71ccffc87430b92bc32a4
- Size of remote file:
- 4.92 GB
- SHA256:
- 6bf52a9f3277146db4e7ae9729eefd18e0f0aed1e92315990fa4f45a1dfb7a08
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