Instructions to use EmnaBou/t5-large-disfluent-jdf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EmnaBou/t5-large-disfluent-jdf with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("EmnaBou/t5-large-disfluent-jdf") model = AutoModelForSeq2SeqLM.from_pretrained("EmnaBou/t5-large-disfluent-jdf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bce4f9b052746876e4812ded33390284528595b5bd5faadea045f98bcef65ec
- Size of remote file:
- 2.95 GB
- SHA256:
- 3a0b60d7aed6d4901c83f1286d1acce9d04f3789b2790756deedd88bb1fc9cfc
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