Instructions to use devvanshhh/flanT5-description-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devvanshhh/flanT5-description-generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("devvanshhh/flanT5-description-generation") model = AutoModelForSeq2SeqLM.from_pretrained("devvanshhh/flanT5-description-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08f5e8e2228ebdb11d47d4dfbb351d5ae4ab0819d9c29a79cbe6cd71ddc2606c
- Size of remote file:
- 308 MB
- SHA256:
- ee25594ec1bdaffc52c6ede7a76b4077a6c4b6020b68e09c21000db301257e16
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