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:
- 28059310267713f4426a1411e1c3054306ed27c24127315835ae9d172e622ae9
- Size of remote file:
- 4.27 MB
- SHA256:
- c280eb9d279e87d5d66217e80c0f4facb5d5a08e8dc52a2ac316bcb0f60ca87a
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