Instructions to use iamatif2003/Rubz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamatif2003/Rubz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="iamatif2003/Rubz")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("iamatif2003/Rubz") model = AutoModel.from_pretrained("iamatif2003/Rubz") - Notebooks
- Google Colab
- Kaggle
| iamatif2003/rubz/ | |
| βββ config.json | |
| βββ pytorch_model.bin (RubzExtreme.ckpt model) | |
| βββ tokenizer_config.json | |
| βββ vocab.txt (custom vocabulary for your tokenizer) | |