Instructions to use hf-internal-testing/tiny-random-FSMTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FSMTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FSMTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FSMTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FSMTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4fcdd7c090509cf35471f7d4df6e71d7637624c5ea65572a756a39f97412eb2
- Size of remote file:
- 4.08 MB
- SHA256:
- ee52bd31b1f64e5ff32001e2d3f8b191256cb0901c1be31a90d459e764ab25d5
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