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
Librarian Bot: Add base_model information to model
#3
by librarian-bot - opened
README.md
CHANGED
|
@@ -5,6 +5,7 @@ tags:
|
|
| 5 |
- generated_from_trainer
|
| 6 |
metrics:
|
| 7 |
- rouge
|
|
|
|
| 8 |
model-index:
|
| 9 |
- name: T5-Base_GNAD_MaxSamples
|
| 10 |
results: []
|
|
|
|
| 5 |
- generated_from_trainer
|
| 6 |
metrics:
|
| 7 |
- rouge
|
| 8 |
+
base_model: Einmalumdiewelt/T5-Base_GNAD_MaxSamples
|
| 9 |
model-index:
|
| 10 |
- name: T5-Base_GNAD_MaxSamples
|
| 11 |
results: []
|