Instructions to use contemmcm/3d6a29693a69f8cf09826201d445a79d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/3d6a29693a69f8cf09826201d445a79d with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/3d6a29693a69f8cf09826201d445a79d") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/3d6a29693a69f8cf09826201d445a79d") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49e18c6e461254ed002e698e5d8be3557e3e3f69733f6eb9b410370981d7b82a
- Size of remote file:
- 16.8 MB
- SHA256:
- 20a46ac256746594ed7e1e3ef733b83fbc5a6f0922aa7480eda961743de080ef
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