Instructions to use midas/gupshup_e2e_t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midas/gupshup_e2e_t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("midas/gupshup_e2e_t5") model = AutoModelForSeq2SeqLM.from_pretrained("midas/gupshup_e2e_t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cc27d3d6f2e45a1559b490ca6532c676581143578161dec2378c8d547d0c694
- Size of remote file:
- 892 MB
- SHA256:
- 4498cb0a7b56d25584de17506a06f8f234ba51af3ef78bfbf3180e8c798e22e2
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