Instructions to use contemmcm/5a621a2ee9af95198a887713042d601b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/5a621a2ee9af95198a887713042d601b with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/5a621a2ee9af95198a887713042d601b") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/5a621a2ee9af95198a887713042d601b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 424d9c5bc4b98a8f254064b29b904b4b5076e0c0dbb7513999d3b45672831363
- Size of remote file:
- 4.49 GB
- SHA256:
- 9bcf64b37ba16f1d9d882e6cf50f66f93de29b4cf6e6ec7918121af65b2c0db2
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