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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 324bfcb416cd616c217bba14eac6dbc93b8045260dc65256f43e5a6bacbe7867
- Size of remote file:
- 4.38 MB
- SHA256:
- f0a8876b932ea69584198675b90c8cbe8f707d6c6318c875d04d43f4e494240e
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