Transformers
PyTorch
English
t5
text2text-generation
semantic-role-labeling
question-answer generation
text-generation-inference
Instructions to use kleinay/qanom-seq2seq-model-baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kleinay/qanom-seq2seq-model-baseline with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kleinay/qanom-seq2seq-model-baseline") model = AutoModelForSeq2SeqLM.from_pretrained("kleinay/qanom-seq2seq-model-baseline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"description": "bilateral, beams=3", "model_type": "t5", "train_dataset": "qanom", "test_dataset": "qanom", "train_epochs": 50, "fp16": true, "batch_size": 12, "source_prefix": "<predicate-type>", "preprocess_input_func": "input_predicate_marker", "use_bilateral_predicate_marker": true, "overwrite_output_dir": true, "num_beams": 3, "wandb_run_name": "2021-12-17--01:20:23_50ep_t5_qanom_new_baseline"} |