Instructions to use akahana/tinybert-javanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akahana/tinybert-javanese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="akahana/tinybert-javanese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("akahana/tinybert-javanese") model = AutoModelForMaskedLM.from_pretrained("akahana/tinybert-javanese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 30.0, | |
| "total_flos": 781486986700800.0, | |
| "train_loss": 6.528281962779993, | |
| "train_runtime": 3948.1737, | |
| "train_samples": 76378, | |
| "train_samples_per_second": 580.354, | |
| "train_steps_per_second": 18.137 | |
| } |