Instructions to use hiaac-nlp/CAPIVARA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use hiaac-nlp/CAPIVARA with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:hiaac-nlp/CAPIVARA') tokenizer = open_clip.get_tokenizer('hf-hub:hiaac-nlp/CAPIVARA') - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b911b65becdc44c45a0c0cfabc3652dd0e47f7af14e6ccaa1b8d6972dae06488
- Size of remote file:
- 1.46 GB
- SHA256:
- 44d6fabf7bdbb4f4b4be3ab95709aef2c7f85630051790f9b120980ab7ca08a0
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