Transformers
PyTorch
German
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use Einmalumdiewelt/T5-Base_GNAD_MaxSamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Einmalumdiewelt/T5-Base_GNAD_MaxSamples with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Einmalumdiewelt/T5-Base_GNAD_MaxSamples") model = AutoModelForSeq2SeqLM.from_pretrained("Einmalumdiewelt/T5-Base_GNAD_MaxSamples") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77fa2cab890f3b40168287ca0e239beda05155a363dfc9c2130ad8853c11b84b
- Size of remote file:
- 892 MB
- SHA256:
- 81274be617d67c9ec77f4b2666f9749a7b063f0eb44769d3a17cb583da9e569a
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