Instructions to use moma1820/DSV-JavaFx-DAPT-CodeBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moma1820/DSV-JavaFx-DAPT-CodeBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="moma1820/DSV-JavaFx-DAPT-CodeBert")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("moma1820/DSV-JavaFx-DAPT-CodeBert") model = AutoModel.from_pretrained("moma1820/DSV-JavaFx-DAPT-CodeBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| Pre Träna CodeBert med JavaFx + Java FXML + JavaFx relaterat logik kod (dvs. Model, Controller för olika JavaFx kod). | |
| Blev ungefär 130 k kod exemplar | |
| ```` | |
| ***** train metrics ***** | |
| epoch = 3.0 | |
| train_loss = 0.4556 | |
| train_runtime = 5:57:43.71 | |
| train_samples = 131945 | |
| train_samples_per_second = 18.442 | |
| train_steps_per_second = 2.305 | |
| ***** eval metrics ***** | |
| epoch = 3.0 | |
| eval_loss = 0.2984 | |
| eval_runtime = 0:01:59.72 | |
| eval_samples = 6944 | |
| eval_samples_per_second = 57.999 | |
| eval_steps_per_second = 7.25 | |
| perplexity = 1.3477 | |
| ```` |