Instructions to use dappyx/QazDistilbertFast-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dappyx/QazDistilbertFast-tokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dappyx/QazDistilbertFast-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| datasets: | |
| - issai/kazqad | |
| language: | |
| - kk | |
| # Model Card for Model ID | |
| Distilbert tokenizer trained on KazQAD | |
| ## Model Details | |
| ### Model Description | |
| - **Model type:** DistilBERT | |
| - **Language(s) (NLP):** Kazakh | |
| ### | |
| ## Training Details | |
| ### Training Data | |
| https://github.com/IS2AI/KazQAD/ | |
| ## Environmental Impact | |
| - **Hardware Type:** TPUv2 | |
| - **Hours used:** Less than a minute | |
| - **Cloud Provider:** Google Colab |