Instructions to use funnel-transformer/medium-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/medium-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/medium-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/medium-base") model = AutoModel.from_pretrained("funnel-transformer/medium-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 382dd0ac172dfd39d7881ef52114352dce78ca36eaf284940552a07aaf90a775
- Size of remote file:
- 463 MB
- SHA256:
- 9369be380a74b8dc099cfe0b74416a1ef27591aa9eaeb2ca2ae6e2e113dd59b1
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