Instructions to use blaxx14/t5-question-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blaxx14/t5-question-generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("blaxx14/t5-question-generation") model = AutoModelForSeq2SeqLM.from_pretrained("blaxx14/t5-question-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
tags:
- generated_from_keras_callback
model-index:
- name: t5-question-generation
results: []
t5-question-generation
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 4.47.0
- TensorFlow 2.18.0
- Tokenizers 0.21.0