Instructions to use google/tapas-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="google/tapas-small")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/tapas-small") model = AutoModel.from_pretrained("google/tapas-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef02e8cc53e7218bbff09ee952f203f1957ee266acbe135d2a62354df1991450
- Size of remote file:
- 117 MB
- SHA256:
- a6860f8a2760452a2ae0f8366236cfe039882c5681ca47b8f7d867357fbcd160
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