Instructions to use CanerCoban/my_awesome_summarization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CanerCoban/my_awesome_summarization_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CanerCoban/my_awesome_summarization_model") model = AutoModelForSeq2SeqLM.from_pretrained("CanerCoban/my_awesome_summarization_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 170bd2636cd7cde21620a5ec511644bd53e31e314e7e667aa01433c2e0ae0020
- Size of remote file:
- 5.43 kB
- SHA256:
- 5a5c81b24522f9a0317251dfaaad1c408edcb8a0335a0ce3ae26d0a3fd7f36b8
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