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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b321dd869c848065b81655caeed7d68e5ce330f7e15e6dbb1041206d7b8dd426
- Size of remote file:
- 708 MB
- SHA256:
- e3c2c6963b6614862f315e1dc939c47a8a867771c5f9327366d77e7416800571
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