Instructions to use hf-tiny-model-private/tiny-random-FSMTModel 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-FSMTModel 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-FSMTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FSMTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FSMTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36786235b507be60a7622b3916c9e390da69446997c2aaccfcab1b09c9b202d7
- Size of remote file:
- 4.07 MB
- SHA256:
- 1fd36c56c27160e5f95f879ab11950a89b4a59dafa30ee11cb4faf8d5882c4f6
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