Instructions to use midas/gupshup_h2e_t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midas/gupshup_h2e_t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("midas/gupshup_h2e_t5") model = AutoModelForSeq2SeqLM.from_pretrained("midas/gupshup_h2e_t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c644864ceb277d22b74d8b9d68bcb2af91a4c1a96c6e558f6290a05681f268e1
- Size of remote file:
- 2.1 kB
- SHA256:
- 82c36d12e99a938e1e2f1a0cb2e0e6cc9bd35af30633a39f3219cb888f0cb134
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