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
File size: 745 Bytes
a1c28bf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | 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
```` |