Instructions to use shenkha/DGSlow_Bartbase_BST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shenkha/DGSlow_Bartbase_BST with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shenkha/DGSlow_Bartbase_BST") model = AutoModelForSeq2SeqLM.from_pretrained("shenkha/DGSlow_Bartbase_BST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 49.99, | |
| "eval_bleu": 1.9931, | |
| "eval_gen_len": 15.1016, | |
| "eval_loss": 3.1176400184631348, | |
| "eval_runtime": 334.1406, | |
| "eval_samples": 5651, | |
| "eval_samples_per_second": 16.912, | |
| "eval_steps_per_second": 0.425, | |
| "train_loss": 2.329808916364397, | |
| "train_runtime": 41571.4467, | |
| "train_samples": 27018, | |
| "train_samples_per_second": 32.496, | |
| "train_steps_per_second": 0.034 | |
| } |