Instructions to use hf-tiny-model-private/tiny-random-PLBartForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-PLBartForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-PLBartForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-PLBartForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12fcf77a2c95a953fc706908fb84cfcfa86b910e1acc0e8d7d78750f239fcc42
- Size of remote file:
- 3.45 MB
- SHA256:
- cc0d1cb7a672cb184ab136bd1ee0f3bfaa8c8a1eff2ad22b4e18141cbf7d5ac5
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