Instructions to use devagonal/t5-flan-semantic-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devagonal/t5-flan-semantic-2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("devagonal/t5-flan-semantic-2") model = AutoModelForSeq2SeqLM.from_pretrained("devagonal/t5-flan-semantic-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcb48131e170d3f9f935feb1d791a37445d9db0f23121b16705024e286cd21a9
- Size of remote file:
- 990 MB
- SHA256:
- d11ccb6a4e8a92555aa0fb4918539578e455ed7a0b8db1f4c7348893309e3754
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