Instructions to use pinglarin/summarization_papers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pinglarin/summarization_papers with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pinglarin/summarization_papers") model = AutoModelForSeq2SeqLM.from_pretrained("pinglarin/summarization_papers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 3.0, | |
| "global_step": 375, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 3.0, | |
| "step": 375, | |
| "total_flos": 1547877482496000.0, | |
| "train_loss": 4.326354817708333, | |
| "train_runtime": 8399.8868, | |
| "train_samples_per_second": 0.179, | |
| "train_steps_per_second": 0.045 | |
| } | |
| ], | |
| "max_steps": 375, | |
| "num_train_epochs": 3, | |
| "total_flos": 1547877482496000.0, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |