Summarization
Transformers
PyTorch
German
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Einmalumdiewelt/T5-Base_GNAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Einmalumdiewelt/T5-Base_GNAD 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="Einmalumdiewelt/T5-Base_GNAD")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Einmalumdiewelt/T5-Base_GNAD") model = AutoModelForSeq2SeqLM.from_pretrained("Einmalumdiewelt/T5-Base_GNAD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d297751f2b55b780f67eb116c2b3c7e9806cecab893faadd8f850f287403e89
- Size of remote file:
- 892 MB
- SHA256:
- 5993aa57c13ea10ef7a997749d6a9d28a3b799e52b546ccd53a89aa289305107
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