Instructions to use funnel-transformer/intermediate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/intermediate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/intermediate")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/intermediate") model = AutoModel.from_pretrained("funnel-transformer/intermediate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4763509fb6c60d7bae30366d6b45bad6cb7b8b55dfdce2abb9e5ab6c40fdf3dc
- Size of remote file:
- 708 MB
- SHA256:
- 37346a2e26cd90f8d8e7e290f5d6212b9a0e873450207c56e495af7473159448
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