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:
- 003947c04e5f8d2aa8cbc9e2b151a138d513eb8de7e61973a7f860625efc7c90
- Size of remote file:
- 558 MB
- SHA256:
- c18d8c21a5bec64b6b9a3f7e9101ff956e9340ebf8201779079425aa1f21a669
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