Instructions to use kejian/cpsc-quark10-3rep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/cpsc-quark10-3rep with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/cpsc-quark10-3rep") model = AutoModel.from_pretrained("kejian/cpsc-quark10-3rep", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 873b481cd339cb206fd19316f6a0de701bf30a62b645d2d7894731cc02c0b948
- Size of remote file:
- 510 MB
- SHA256:
- c1e0a8eb6a5168ef8f6200621f6fc266e8a0e94f41103da0c387f5c6cf9cb0f2
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