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
- Xet hash:
- 57ad344de1b675b1ef62c102cf0c1b367f4cee4b1669cb5d30a0f2d0d7fa5a28
- Size of remote file:
- 188 MB
- SHA256:
- 0e3f905bc8155c45f66d7aba26d2f04d85a5f18a948b4080e086eaa7226e7eac
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