Instructions to use hf-internal-testing/tiny-random-TapasModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TapasModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-TapasModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-TapasModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-TapasModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b58d37ee15fef96b9efe6b6a12d6754a392015fd611a86b16995e10969d8fddd
- Size of remote file:
- 4.26 MB
- SHA256:
- fd9f8e6d6be268af19b8b0addd67215e9da93d5140f960957e783b83e7a357fd
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