Instructions to use bubblecookie/samsum_trained_t5_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bubblecookie/samsum_trained_t5_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bubblecookie/samsum_trained_t5_model") model = AutoModelForSeq2SeqLM.from_pretrained("bubblecookie/samsum_trained_t5_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43b0e4eae4d2d00f2f8e3dbf12250f5bdc458f1bda598b494fa0c858a181184e
- Size of remote file:
- 242 MB
- SHA256:
- d5e6078aa5eba604b265856d2c3fde356d5e4e7510d08ddfc58e48e04981c6f2
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