Instructions to use ndaheim/cima_joint_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndaheim/cima_joint_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ndaheim/cima_joint_model") model = AutoModelForSeq2SeqLM.from_pretrained("ndaheim/cima_joint_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36c9029cc24230296e21308173b13d115e52582e3e4d1fdffe09830c2ce1d266
- Size of remote file:
- 2.93 kB
- SHA256:
- b6d0dd5195a5c72eed3cf01ad4025ca6a983050b6d3743b3153b17a436650aa6
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