Instructions to use Prerna2055/T5_ModelCompression_Federated_Learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prerna2055/T5_ModelCompression_Federated_Learning with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Prerna2055/T5_ModelCompression_Federated_Learning") model = AutoModelForSeq2SeqLM.from_pretrained("Prerna2055/T5_ModelCompression_Federated_Learning") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 049f4fa73c2a0e7535276fcd93d92ff5fc3d00e5dc0e612e5f3f54b64127f097
- Size of remote file:
- 242 MB
- SHA256:
- f67910e661f9bb128572796df78bf59009a805e7a73d39ee952ec52c4006f7e1
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