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:
- 8b2db267dfa9ecc1c7a079bf66ef3f3f7d4dc14f7e6bd1cedd4d9f416539032b
- Size of remote file:
- 3.76 MB
- SHA256:
- 5c7a2a0eba3f1dc0797f5aaf543aa12cb834e4145032d31b444e2456e596dbe4
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