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:
- 97e3195125a2b3abd8b7eeb7bedf2e498b3ce9b28aa28f119cce4493db9ce659
- Size of remote file:
- 797 kB
- SHA256:
- bbd1f495eea99c8e21ae086d9146e0fa7b096c3dfdd9ba07ab8b631889df5c9b
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