Instructions to use shivam12/t5_small_pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shivam12/t5_small_pubmed with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shivam12/t5_small_pubmed") model = AutoModelForSeq2SeqLM.from_pretrained("shivam12/t5_small_pubmed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95c9b1d0004f416c2985717ccb35e7e0ce4ebdfe074018e68833ccca0d79ae82
- Size of remote file:
- 242 MB
- SHA256:
- 2f9e8ba25d3d6e1433d693a00edb8028b57c5b01114c81f5cb93ba093527f67f
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