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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "predict_gen_len": 52.516, | |
| "predict_loss": 2.131106376647949, | |
| "predict_rouge1": 26.7775, | |
| "predict_rouge2": 8.2523, | |
| "predict_rougeL": 18.6904, | |
| "predict_rougeLsum": 23.2921, | |
| "predict_runtime": 251.4989, | |
| "predict_samples": 1500, | |
| "predict_samples_per_second": 5.964, | |
| "predict_steps_per_second": 0.748 | |
| } |