Instructions to use prithivida/passive_to_active_styletransfer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivida/passive_to_active_styletransfer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("prithivida/passive_to_active_styletransfer") model = AutoModelForSeq2SeqLM.from_pretrained("prithivida/passive_to_active_styletransfer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7365b742825d0110e7379f960cc4679c3c6ea3549c4fe5a2adae7b618de1ffa2
- Size of remote file:
- 2.54 kB
- SHA256:
- 29e171197d8d669538df17761cf77976613eb780c0327d7b4cf841b6037d9014
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