Instructions to use midas/gupshup_e2e_bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midas/gupshup_e2e_bart with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("midas/gupshup_e2e_bart") model = AutoModelForSeq2SeqLM.from_pretrained("midas/gupshup_e2e_bart") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27d07280d31f6eb9d5aec11c3f94274893660f6e243a290b469ca71f2876d641
- Size of remote file:
- 558 MB
- SHA256:
- 2efdeeaf157087166b2f526738e0e28c6786ae9c2f6f579d734d7d487e496532
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