Instructions to use google/tapas-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="google/tapas-mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/tapas-mini") model = AutoModel.from_pretrained("google/tapas-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from google/tapas-mini: direct link, hf CLI and curl.
- Browser
- Download file 45.8 MB
-
https://huggingface.co/google/tapas-mini/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://google/tapas-mini/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/tapas-mini/resolve/main/pytorch_model.bin
45.8 MB
- Xet hash:
- d9ba97efd073f9434589a16cc1ede8596ae42370b99b1c405fbacf6a508a9883
- Size of remote file:
- 45.8 MB
- SHA256:
- 6df9ec100e3ec0d35aa862f7cc22c71b249d4ab337892e846620204893f9a681
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