Instructions to use contemmcm/a50e0479df31a6b42995051c03abb9ef with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/a50e0479df31a6b42995051c03abb9ef with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/a50e0479df31a6b42995051c03abb9ef") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/a50e0479df31a6b42995051c03abb9ef", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7c93397acf7b7ec8d7d960e02cfbdc08a0c33a495a1451deb285f066baab5f8
- Size of remote file:
- 6.1 kB
- SHA256:
- ff0b974a3b6656758e3844013f027eb14c37bced1794ddc73db4367b55372c16
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