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:
- 79fce6d54e9594b7b356c8a397d72f3c55cdbeb5c2f7cb87738faa27df76f5d6
- Size of remote file:
- 3.85 MB
- SHA256:
- b2aacdd2dd2b157773af3b8366cbefb1a4785bf193a8ae67e025bfd43baab82a
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