Instructions to use hf-tiny-model-private/tiny-random-ProphetNetForConditionalGeneration 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-ProphetNetForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ProphetNetForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-ProphetNetForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89add051c95acab3cdb342e177347902ecb6755cc928d7db9a22aa31fb3997f2
- Size of remote file:
- 2.14 MB
- SHA256:
- 84e6f9b3d408c6e9d03b6220be8d0bc93f63e7c4d245b44d6df92bba235706db
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.