Instructions to use google/tapas-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="google/tapas-tiny")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/tapas-tiny") model = AutoModel.from_pretrained("google/tapas-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 836c6759928ca2afa9d437355e92197e758feba01158eb19d9973f9249861e5b
- Size of remote file:
- 18.1 MB
- SHA256:
- f2dec792b1ebacd84689e79d844c9a9cafcbee318d2daf463ced833e3e3f9710
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.