Instructions to use ppang/model5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppang/model5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ppang/model5") model = AutoModelForSeq2SeqLM.from_pretrained("ppang/model5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "output_dir": "/content/drive/My Drive/workspace/TS_PP/experiments/1601582154282931", | |
| "model_name_or_path": "t5-base", | |
| "tokenizer_name_or_path": "t5-base", | |
| "max_seq_length": "256", | |
| "learning_rate": "0.0003", | |
| "weight_decay": "0.1", | |
| "adam_epsilon": "1e-08", | |
| "warmup_steps": "5", | |
| "train_batch_size": "6", | |
| "eval_batch_size": "6", | |
| "num_train_epochs": "5", | |
| "gradient_accumulation_steps": "16", | |
| "n_gpu": "1", | |
| "early_stop_callback": "False", | |
| "fp_16": "False", | |
| "opt_level": "O1", | |
| "max_grad_norm": "1.0", | |
| "seed": "12" | |
| } |