Instructions to use hf-tiny-model-private/tiny-random-ProphetNetModel 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-ProphetNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-ProphetNetModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ProphetNetModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ProphetNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba9e5078fd908ea94f1c9c2338216ccb5bbed850343e392e7b357b7a570f3c46
- Size of remote file:
- 2.1 MB
- SHA256:
- 501cd2c8c3515a53c8b2eb240291c878397a272a4a37c4b7af6c1596c3ffffe3
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