Transformers
TensorFlow
Safetensors
t5
text2text-generation
generated_from_keras_callback
text-generation-inference
Instructions to use kadasterdst/querygenerator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kadasterdst/querygenerator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kadasterdst/querygenerator") model = AutoModelForSeq2SeqLM.from_pretrained("kadasterdst/querygenerator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: querygenerator | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should | |
| probably proofread and complete it, then remove this comment. --> | |
| # querygenerator | |
| This model was trained from scratch on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - optimizer: None | |
| - training_precision: float32 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.48.3 | |
| - TensorFlow 2.14.1 | |
| - Datasets 2.14.6 | |
| - Tokenizers 0.21.0 | |