Instructions to use hf-tiny-model-private/tiny-random-MarianModel 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-MarianModel 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-MarianModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MarianModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MarianModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f48c26f5273e5b9b2fcfb74a163c0ffdfe1c37801d158ea86e842f978e44854e
- Size of remote file:
- 3.78 MB
- SHA256:
- eed3642e1b26518f9b1a7b1bf720cf6cc2a545879876d83cc33075e83b906561
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