Instructions to use google/tapas-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="google/tapas-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/tapas-base") model = AutoModel.from_pretrained("google/tapas-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 692280b7894d721ff9203d25e5c95ffef02ac3bd802e626a6dec1d7b972ce581
- Size of remote file:
- 443 MB
- SHA256:
- 8b15876bed48233a5f2ae6379e016e439edd92d84cf5f9719345975c7341cc1d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.