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:
- e779d4d3e75ebb24c92bace17daa0176084258bc7e942641ee5b69433b624b28
- Size of remote file:
- 3.47 MB
- SHA256:
- 3f6599cb7aff65500c5f74b5da41f29c3f8d24c4bde24c9951c1e3d6886c32c9
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