Instructions to use hf-tiny-model-private/tiny-random-TapasModel 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-TapasModel 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-TapasModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-TapasModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-TapasModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ac50069c2b66323f90ed88389b81e45d6330011d18840afb31ddb2404597548
- Size of remote file:
- 4.27 MB
- SHA256:
- 487a487ac1bb68bfb390661e0d92483b6dd10ee30ecba7fdc9f773160adad902
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