Instructions to use contemmcm/5f1361050d64792ce520deecccdcac6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/5f1361050d64792ce520deecccdcac6b with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("contemmcm/5f1361050d64792ce520deecccdcac6b") model = AutoModelForSeq2SeqLM.from_pretrained("contemmcm/5f1361050d64792ce520deecccdcac6b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e40f30b8743accd14f3ac775c6ef1eb3c8bec275da9027e3eb00471929a4a2c8
- Size of remote file:
- 808 kB
- SHA256:
- 65ad5af01db2eb3d54ce33e997cc19269963aed88587ac2c9508c7b91547a306
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