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:
- b184985e50f97b5d782bd627a01475c10ca0c687576154a535135ba29d52b634
- Size of remote file:
- 4.26 MB
- SHA256:
- eba9fb2dda8a42cf9f14dd407c20f230959cb4f90e4bec2ee4f7c0632ecd814a
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